Congestion mitigation at railroad-highway at-grade crossings

Congestion Mitigation at Railroad-Highway At-Grade Crossings
Final Report 557
Prepared by: Craig A. Roberts, Ph.D., P.E., Principal Investigator Jamie Brown-Esplain, Research Engineer AZTrans: The Arizona Laboratory for Applied Transportation Research Northern Arizona University Department of Civil and Environmental Engineering Flagstaff, AZ 86004-5600
October 2005
Prepared for: Arizona Department of Transportation 206 South 17th Avenue Phoenix, Arizona 85007 In cooperation with U.S. Department of Transportation Federal Highway Administration
The contents of this report reflect the views of the authors who are responsible for the facts and accuracy of the data presented herein. The contents do not necessarily reflect official views or policies of the Arizona Department of Transportation or the Federal Highway Administration. The report does not constitute a standard, specification, or regulation. Trade or manufacturers' names that appear herein are cited only because they are considered essential to the objectives of the report. The U.S. Government and the State of Arizona do not endorse products or manufacturers.
This ATRC report is available on the Arizona Department of Transportation's Internet site.
Technical Report Documentation Page
1. Report No.
FHWA-AZ-05-557
4. Title and Subtitle
2. Government Accession No.
3. Recipient's Catalog No. 5. Report Date
Congestion Mitigation at Railroad-Highway At-Grade Crossings
October 2005
6. Performing Organization Code
7. Author
8. Performing Organization Report No.
Craig A. Roberts, Ph.D., P.E., Principal Investigator Jamie Brown-Esplain, Research Engineer
9. Performing Organization Name and Address 10. Work Unit No.
AZTrans: The Arizona Laboratory for Applied Transportation Research Northern Arizona University Civil and Environmental Engineering Department P.O. Box 15600 Flagstaff, AZ 86011-5600
12. Sponsoring Agency Name and Address
11. Contract or Grant No. SPR-PL-1(63)557 JPA 02-209 / R0557 15P
13. Type of Report & Period Covered
ARIZONA DEPARTMENT OF TRANSPORTATION 206 S. 17th Avenue, Phoenix, Arizona 85007 ADOT Project Manager: Stephen R. Owen, P.E. *with additional funding support from the City of Flagstaff and Northern Arizona University
15. Supplementary Notes
FINAL REPORT March 2003 - November 2005
14. Sponsoring Agency Code
Prepared in cooperation with the U.S. Department of Transportation, Federal Highway Administration
16. Abstract ?
Rapid population growth in Arizona has created several large residential areas that rely on the State highways to provide their primary, daily commuting route. When these commuter routes cross an at-grade railroad crossing, a train passing during peak traffic hours often causes severe congestion. State resources are inadequate to provide flyovers for all of these train crossings and their numbers are forecast to increase. The safety and congestion problems arising from these commuter at-grade crossings are the focus of this research. A study site was selected, train and traffic data were collected, a microscopic traffic simulation model was prepared, and an Early Warning System (EWS) algorithm was developed. The EWS algorithm gives "extra" green time to (train) conflicting traffic movements before the train arrives, taking the time from the other movements. Five cases were studied, each having two to six scenarios. Four major variables were studied: (1) crossing gates down time, (2) length of time the MOEs were collected, (3) conflicting movements traffic volumes, and (4) predicted arrival time error. The EWS algorithm was also successfully programmed into a NEMA controller using Hardware-in-the-Loop to couple it to the simulation model. Four generalizations are tentatively supported by the results but additional site studies are required for verification. First, the complex dynamic interplay of geometrics and train and traffic volumes makes the EWS effectiveness highly site dependent. Second, there must be enough pre-train vehicles present on conflicting movements that derive delay improvement to overcome the increase in delay to the other movements. Third, for safety reasons, an increase in overall intersection delay caused by the EWS may be justified to reduce long queues from backing-up into other intersections or onto freeways. Fourth, rather than control signal timing, the EWS may be used to reduce congestion by alerting drivers with a DMS of a train's imminent arrival so they can take alternate routes. While the EWS was ineffective for the study site, the results may have been confounded by insufficient pre-train queue sizes and lack of a single dominant commuter movement (the study site had strong cross flows). A follow-up study is recommended at a site with more favorable geometry and traffic volumes.
17. Key Words 18. Distribution Statement
Microscopic Simulation Models, At-Grade Highway-Railroad Crossings, Railroad Grade Crossings, Preemption, Hardware-inthe-Loop, HIL, VISSIM, CID, DSM, ITS, Model Calibration
19. Security Classification 20. Security Classification
Document is available to the U.S. Public through the National Technical Information Service, Springfield, Virginia, 22161
21. No. of Pages 22. Price
23. Registrant's Seal
Not Applicable
Unclassified
Unclassified
104
SI* (MODERN METRIC) CONVERSION FACTORS
APPROXIMATE CONVERSIONS TO SI UNITS
Symbol in ft yd mi in2 ft2 yd2 ac mi2 fl oz gal ft3 yd3 When You Know inches feet yards miles square inches square feet square yards acres square miles fluid ounces gallons cubic feet cubic yards Multiply By To Find millimeters meters meters kilometers square millimeters square meters square meters hectares square kilometers milliliters liters cubic meters cubic meters Symbol mm m m km mm2 m2 m2 ha km2 mL L m3 m3 Symbol mm m m km mm2 m2 m2 ha km2 mL L m3 m3
APPROXIMATE CONVERSIONS FROM SI UNITS
When You Know millimeters meters meters kilometers square millimeters square meters square meters hectares square kilometers milliliters liters cubic meters cubic meters Multiply By To Find inches feet yards miles square inches square feet square yards acres square miles fluid ounces gallons cubic feet cubic yards Symbol in ft yd mi in2 ft2 yd2 ac mi2 fl oz gal ft3 yd3
LENGTH
25.4 0.305 0.914 1.61
LENGTH
0.039 3.28 1.09 0.621
AREA
645.2 0.093 0.836 0.405 2.59
AREA
0.0016 10.764 1.195 2.47 0.386
VOLUME
29.57 3.785 0.028 0.765
VOLUME
0.034 0.264 35.315 1.308
NOTE: Volumes greater than 1000L shall be shown in m3.
MASS
oz lb T ounces pounds short tons (2000lb) 28.35 0.454 0.907 grams kilograms megagrams (or "metric ton") Celsius temperature g kg mg (or "t")
?
MASS
g kg Mg grams kilograms megagrams (or "metric ton") Celsius temperature 0.035 2.205 1.102 ounces pounds short tons (2000lb) oz lb T
?
TEMPERATURE (exact)
Fahrenheit temperature foot-candles foot-Lamberts poundforce poundforce per square inch 5(F-32)/9 or (F-32)/1.8
F
C
?
TEMPERATURE (exact)
1.8C + 32 Fahrenheit temperature foot-candles foot-Lamberts
C
?
F
ILLUMINATION
fc fl lbf lbf/in2 10.76 3.426 4.45 6.89 lux candela/m2 Newtons kilopascals lx cd/m2 N kPa lx cd/m2 N kPa lux candela/m2
ILLUMINATION
0.0929 0.2919 0.225 0.145 fc fl
FORCE AND PRESSURE OR STRESS
FORCE AND PRESSURE OR STRESS
Newtons kilopascals poundforce lbf poundforce per lbf/in2 square inch
SI is the symbol for the International System of Units. Appropriate rounding should be made to comply with Section 4 of ASTM E380
TABLE OF CONTENTS
EXECUTIVE SUMMARY 1. INTRODUCTION 1.1. MOTIVATION FOR RESEARCH 1.2. SCOPE OF THIS RESEARCH 1.3. ORGANIZATION OF THE REPORT 2. PROBLEMS WITH AT-GRADE HIGHWAY-RAILROAD CROSSINGS 2.1. TRAIN SAFETY 2.2. VEHICLE SAFETY 2.3. VEHICLE CONGESTION 3. SITE SELECTION, GEOMETRICS, AND TRAFFIC 3.1. SELECTION OF THE STUDY SITE 3.1.1. Railroad Equipment and Operations Used at the Site 3.1.2. Traffic Signal Equipment and Operations Used at the Site 3.2. SITE GEOMETRICS AND MODIFICATIONS FOR MODEL 3.2.1. Current Geometrics at the Study Site 3.2.2. Modified Tee Intersection Geometrics Used for the Study 3.3. VEHICLE TRAFFIC USED IN THE MODEL 3.3.1. Data Collection Procedure 3.3.2. Adjustments Made To Data Provided By TDS 3.3.3. Data Used in the VISSIM Model For Calibration And Validation 3.3.4. Modified Data Used in the VISSIM Model for Study Cases 3.4. RAILROAD TRAIN CHARACTERISTICS USED IN THE MODEL 4. MODEL DEVELOPMENT 4.1. SELECTION OF THE MODELING ENVIRONMENT 4.2. VISSIM MODEL CALIBRATION 4.2.1. Establishment of Calibration Parameters 4.2.2. The Calibration Process 4.3. VISSIM MODEL VERIFICATION 5. EARLY WARNING SYSTEM (EWS) 5.1. EARLY WARNING SYSTEM DESIGN CONSIDERATIONS 5.2. EWS DETECTION SUBSYSTEM 5.2.1. Radar Detection and Wireless Communication 5.2.2. Time Domain Reflectometry (TDR) Detection 5.3. EWS PREDICTION SUBSYSTEM 1 7 7 9 9 11 11 12 14 15 15 15 19 22 22 23 24 24 26 28 30 30 33 33 33 34 39 39 41 41 41 41 42 43
EWS CONGESTION MITIGATION SUBSYSTEM 5.4.1. Principle of Costs and Benefits 5.4.2. Measurement of Costs versus Benefits 5.4.3. Method to Capture Costs versus Benefits -- Before and After Study 5.4.4. Stochastic Models Require Multiple Runs 5.4.5. Principle of Availability of Vehicles to Receive Benefit 5.5. EWS SAFETY SUBSYSTEM 6. EWS CONGESTION MITIGATION ALGORITHM DEVELOPMENT 6.1. ALGORITHM DEVELOPMENT 6.1.1. EWS Algorithm Logic Concepts 6.1.2. Application of the Algorithm at the Study Site 6.1.3. Limitations Imposed on the Algorithm 6.2. INDEPENDENT ALGORITHM TESTING 7. BEFORE AND AFTER RESULTS 7.1. PARAMETERS USED FOR EWS CONGESTION MITIGATION 7.2. BEFORE AND AFTER CASES STUDIED 7.3. SUMMARY OF RESULTS 7.3.1. Duration Of Gates Down At Crossing 7.3.2. Duration Of MOE Period 7.3.3. Vehicle Traffic Volume Increases On Conflicting Movements 7.3.4. Early and Late Train Arrivals Versus Predicted On-Time Arrival 7.3.5. Impacts on Targeted Queue Lengths 8. HARDWARE-IN-THE-LOOP (HIL) TESTING 8.1. BENEFITS OF HIL TESTING 8.2. METHODOLOGY AND EQUIPMENT 8.3. IMPLEMENTATION USING NEMA TRAFFIC CONTROLLER 8.4. SUMMARY OF RESULTS 9. CONCLUSIONS 9.1. EFFECTIVENESS HIGHLY DEPENDENT ON THE SITE 9.2. VEHICLES MUST BE PRESENT TO USE THE EWS GREEN TIME 9.3. QUEUE LENGTH MAY SUPPORT INCREASED EWS DELAY 9.4. EWS MAY BE USEFUL FOR OTHER PURPOSES 10. RECOMMENDATIONS
5.4.
44 44 45 45 45 46 46 49 49 49 50 51 52 53 53 53 57 57 60 62 64 66 69 69 70 71 73 75 75 76 76 76 77
APPENDIX A. LITERATURE REVIEW A.1. MICROSCOPIC TRAFFIC SIMULATION MODELS A.2. ALGORITHM DEVELOPMENT A.3. HIGHWAY-RAILROAD CROSSING SIGNAL PREEMPTION A.4. HIGHWAY-RAILROAD CROSSING ISSUES A.5. HARDWARE-IN-THE-LOOP SIMULATION APPENDIX B. RAILROAD TRAFFIC DATA COLLECTION B.1. RAILROAD DATA COLLECTION METHODOLOGY B.2. GENERAL CHARACTERISTICS OF RAILROAD TRAFFIC DATA APPENDIX C. EWS CONGESTION MITIGATION ALGORITHM PROGRAMMING C.1. VISSIM MACRO LANGUAGE C.2. SYNOPSIS OF ALGORITHM LOGIC C.2.1. Position of Train Corresponds to Three States REFERENCES
79 79 81 82 83 84 85 85 85 89 89 89 90 95
LIST OF TABLES
Table 1: Table 2: Table 3: Table 4: Project 557: Technical Advisory Committee Members Overview Of Case Attributes Overview Of Case Runs Train Crossing Summary At The Study Site 10 55 56 86
LIST OF FIGURES
Figure 1: Aerial Photos Of The Study Site ...................................................................... 16 Figure 2: Photos Of The At-Grade Crossing At The Study Site...................................... 17 Figure 3: Photo Of At-Grade Crossing Equipment At The Study Site............................ 18 Figure 4: Photo Of The Intersection At The Study Site .................................................. 22 Figure 5: Vehicle Traffic Data Collection Using Pneumatic Hoses. ............................... 25 Figure 6: Video Cameras Location Map.......................................................................... 27 Figure 7: "Scissor Lifts" Aided In Obtaining Adequate Video. ...................................... 28 Figure 8: Study Intersection with Vehicle Movement Controller Numbers.................... 30 Figure 9: VISSIM Model Showing Data Collection Points............................................. 35 Figure 10: VISSIM Model Screen Display Showing Route 66/Enterprise Showing Reduced Speed Areas, Links, And Connectors .............................................. 36 Figure 11: VISSIM Model Screen Display Showing Enterprise/Butler Showing Reduced Speed Areas, Links, And Connectors .............................................. 37 Figure 12: VISSIM Model Screen Display Showing Huntington Slip Lane Showing Reduced Speed Area, Links, And Connectors................................................ 38 Figure 13: Delay For Different Gates Down Durations Using EWS On WB LT ........... 59 Figure 14: Delay For Different Gates Down Durations Using EWS On NB .................. 59 Figure 15: Delay For Different MOE Duration Periods Using EWS On WB LT........... 61 Figure 16: Delay For Different MOE Duration Periods Using EWS On NB.................. 61 Figure 17: Delay For Increased Relative Volumes Using EWS On WB LT................... 63 Figure 18: Delay For Increased Relative Volumes Using EWS On NB ......................... 63 Figure 19: Delay For Early, Late, And On-Time Arrivals Using EWS On WB LT ....... 65 Figure 20: Delay For Early, Late, And On-Time Arrivals Using EWS On NB .............. 65 Figure 21: Impact On Targeted Queue Using EWS On WB LT .................................... 67 Figure 22: Impact On Targeted Queue Using EWS On NB........................................... 67 Figure 23: Hardware-In-The-Loop Schematic Using McCain-NIATT CID II ............... 70 Figure 24: Econolite Controller--CID II--VISSIM Model Setup .................................... 71 Figure 25: Modeled Volumes During Peak 30 Minutes Centered On Train Arrival....... 75 Figure 26: Empirical CDF Of Train Headways At The Study Site ................................. 87 Figure 27: Empirical CDF Of Gates-Down At The Study Site ....................................... 88 Figure 28: NEMA 8-Phase Controller Configuration...................................................... 90
SIGNIFICANT TERMS, ACRONYMS, AND ABBREVIATIONS
ADOT AM Peak and PM Peak Approach At-grade Crossing ATRC AZTrans Arizona Department of Transportation The peak vehicle traffic flows that typically occur in the morning due to home-to-work trips and in the evening due to work-to-home trips. All lanes of traffic moving towards an intersection from one direction. The intersection of a roadway and a railroad track(s) at the same elevation or grade. Arizona Transportation Research Center: administers the research activity of ADOT and the publication of the results. The Arizona Laboratory of Transportation, the research unit at Northern Arizona University, Department of Civil and Environmental Engineering that conducted this study. Burlington Northern Santa Fe Railway Company Cumulative Distribution Function is the function that gives the cumulative frequency or cumulative probability of a random variable. Computer Interface Device is a combination of hardware and software that allows an actual traffic signal controller to be linked to a computer and operate as part of a traffic simulation model. In this study, an at-grade crossing used by a large number of travelers making daily home-to-work and work-to-home trips. In this study, a traffic movement that has to cross the railroad track before entering or after leaving a nearby intersection. See "Nonconflicting Moment." Early Warning System ? a software or algorithm used to control an intersection's traffic signal system before a train arrives at a nearby at-grade crossing. Federal Highway Administration When a roadway is grade separated to cross a railroad, by either passing over the railroad or the railroad passing over the roadway. Federal Railroad Administration Hardware-in-the-Loop simulation refers to a computer simulation in which some of the components of the simulation have been replaced with actual hardware. The hardware is fully functioning, responding to the simulation environment as if it were a real environment. Intelligent Transportation System
BNSF CDF CID
Commuter At-grade Crossing Conflicting Movement EWS
FHWA Flyover FRA HIL
ITS
MOE Movement
Measure of Effectiveness A path through an intersection. For this study site (see Figure 8), the principal traffic movements and directionalities are defined as follows: NB: Northbound; SB: Southbound; EB: Eastbound; WB: Westbound LT: Left Turn; RT: Right Turn; TH: (Straight) Through
MUTCD NEMA Nonconflicting Movement PM Preemption Control Run
Manual of Uniform Traffic Control Devices National Electrical Manufacturers Association A traffic movement that does not have to cross the railroad track before entering or after leaving a nearby intersection. See "Conflicting Movement." Performance Measure The transfer of normal operation of a traffic control signal to a special control mode of operation. Microscopic traffic simulation software generates a result using several stochastic processes. In order to generate an approximately random number for these processes, a beginning number is used. This beginning number is called a seed and the generation of the results is called a run. See "Run." Technical Advisory Committee Project sub-consultant, Traffic Data Systems, Inc. Vehicle Actuated Programming is the name of the macro language for VISSIM. A microscopic traffic simulation modeling software originally developed in Germany and maintained in the United States by PTV America, Inc.
Seed TAC TDS VAP VISSIM
EXECUTIVE SUMMARY
Several major Arizona highways are located parallel to active railroads. Population growth in the State has been rapid over the last 40 years and is projected to continue. Most of this growth has occurred in the major cities and towns, pushing them outwards along the State highway routes. This has created many large residential areas that rely on State highways to provide the primary, and often only, daily commuting route. When these commuter routes cross an at-grade railroad crossing, a train passing during peak traffic hours often causes congestion that delays traffic and may back queues into adjacent intersections or onto freeways, causing operational and safety concerns for the Arizona Department of Transportation (ADOT). Additional contributing factors to the congestion and safety concerns are the increasing traffic on the railroad lines and the increasing number of these types of crossings, which far outstrip the State's ability to provide grade-separated railroad crossings. The safety and congestion problems arising from these commuter at-grade crossings are the focus of this research for ADOT, which investigates these central issues: Research Question: Can solutions be applied at a signalized intersection, before a train passes a nearby at-grade highway-railroad crossing, that will mitigate the congestion that will occur after the train has passed? Furthermore, can this be accomplished using a standard traffic signal controller? Operational Issues The current organizational and operating systems of the railroad company and the agency that operates adjacent traffic signals have evolved over time, and each may resist change for safety and liability reasons. At an at-grade crossing, the right-of-way corridor is owned by the railway company, which also owns and operates the gates and lights that comprise the active system that alerts drivers to an approaching train. The traffic signal system at the nearby intersection is owned and operated by the city, county, or state agency that owns the roadway. The railroad's warning control system and the traffic signal control system are not integrated, and operate independently. It is critical for the nearby intersection traffic signal system to know of an approaching train so that it can take appropriate action to reduce safety problems. This is currently done by the railroad control system sending a signal to the traffic signal control system indicating a train is approaching the crossing, and later sending another signal that the train has cleared the crossing. When this signal is received, the traffic signal system operates independently to address the situation by altering its intersection control scheme in a manner known as train preemption, or simply "preemption." During preemption, the traffic signal control system does four things: (1) it safely interrupts whatever movements are currently timing and gives the green to the movements that are queued across the railroad tracks, (2) it then switches to a sequence that gives green only to non-conflicting movements and withholds green from all conflicting movements while the train passes (a conflicting movement is one that has to cross the railroad track before entering or after leaving the nearby intersection), (3) after the train has passed, it switches to a designated movement (typically the one that is 1
waiting behind the crossing gates), and (4) lastly, it places a call on another designated movement while releasing control back to the normal cycle sequence. The train preemption control scheme's primary purpose is safety; congestion mitigation is a secondary goal that occurs only after the train has passed. When vehicle volumes over the at-grade crossing are sufficiently large, and/or when the duration and/or frequency of the passing trains is sufficiently high, the preemption control scheme may be insufficient to clear all of the vehicles. This creates congestion that may cause operational problems for the roadway system. Depending on the geometrics involved, vehicle queues may extend back considerable distances into other intersections, or along freeway ramps onto the freeway itself. In some cases, it can take several cycles for queued vehicles to clear the intersection, causing considerable delay to drivers. The congestion problem is exacerbated if a second train passes before the congestion from the first train clears. Study Site Geometrics and Traffic Study site candidates required two primary characteristics: (1) they must be a commuter at-grade crossing and (2) the nearby signalized intersection must be on a State highway. Ideally the site would have severe congestion caused by passing trains. The study site selected was ADOT's Route 66 intersection with Enterprise Road in Flagstaff, Arizona. This site was chosen when the City of Flagstaff became an active secondary sponsor for the research. In retrospect, however, this intersection proved less than ideal due to its unique geometry and traffic patterns. The study intersection is a "tee" with Route 66 running east-west, and Enterprise Road as the north-south leg that ends at the intersection (see Figure 1). The east-west railroad tracks are parallel to Route 66, and cross Enterprise Road approximately 75 feet south of the intersection. The geometrics of Enterprise were recently upgraded to two northbound left-turn lanes (NB LT) and one northbound right-turn lane (NB RT). The basic Route 66 geometrics were unchanged, consisting of two EB TH (eastbound through) lanes, one EB RT lane, two WB TH (westbound through) lanes, and one WB LT lane. Each of these movements has its own signal head except EB RT, which has its own stacking lane but no signal head. The normal signal cycle at the intersection has three phases and sequence in this order: (1) WB LT, WB TH, and NB RT; (2) EB TH and EB RT to move also; and (3) NB TH and NB RT. In the standard NEMA controller used at the site, NB RT operates as an overlap with WB LT and also as an overlap with NB LT. It is allowed to do this by giving it its own phase designation, but this phase only operates as an overlap. Right turns on red after stop are allowed for both the NB RT and the EB RT. The railroad crossing is owned and operated by the Burlington Northern Santa Fe (BNSF) Railway Company. It is an active crossing using advance warning signs, crossbucks, pavement markings, bells, gates, and flashing lights. BNSF's control system sends the signal to the intersection traffic signal control system indicating a train is approaching and another signal indicating the train has cleared the crossing. These signals allow ADOT to begin and end the special train preemption traffic control scheme.
2
An Early Warning System (EWS) was developed for this study to address the research question. After applying the EWS to the simulation model developed for the study site, it became apparent that the recent geometric improvements to the study site reduced the congestion sufficiently to mask any congestion mitigation improvement potentially attributable to the EWS. The study site simulation was therefore altered to reflect its geometry before the recent construction and restriping. This changed the study site model by (1) reducing the NB LT to only one lane, (2) increasing the length of the EB RT stacking lane by about 25 feet, and (3) reducing the Enterprise Road SB (southbound) lanes leaving the intersection from two to one. The railroad-crossing model was also simplified to two mainline tracks, by eliminating two other infrequently used tracks. Vehicle traffic data was collected continuously at the site for all movements over a threeday period, including counts and video tape. The railroad (BNSF) was a partner in the research, and provided data of all train traffic at the site for a typical seven-day period. Traffic Simulation Model Development The VISSIM traffic simulation model was used in the study for the following four reasons: (1) proven ability to model both train and vehicle traffic, (2) ability to model detailed traffic behavior, (3) ability to modify the model to incorporate intelligent transportation system (ITS) devices, and (4) proven ability to use hardware-in-the-loop (HIL) techniques to test traffic signal controllers. A VISSIM model was prepared for the study site, and was calibrated and validated using two different data sets extracted from the three days of traffic data. Development of the model was the major portion of the research effort, requiring significant study time and resources. Early Warning System An ideal EWS would have four characteristics: (1) simple and inexpensive to design, build, and install; (2) easily maintained by existing traffic signal technicians; (3) unilaterally controlled by the highway agency without need for any changes to the railroad control system; and (4) able to retain the time-tested safety aspects of the current at-grade crossing highway and railroad preemption control systems. The EWS developed for this research contains these four characteristics and uses four subsystems to provide (1) detection, (2) prediction, (3) congestion mitigation, and (4) safety. Conceptually two different types of sensor devices could be used for the detection subsystem: (1) Doppler radar and (2) time domain reflectometry (TDR). The Doppler radar detector has been used for train detection in previous research. It is pole-mounted in a fixed location adjacent to the railroad right-of-way, far from the at-grade crossing. It transmits data about a passing train through wireless transmission to the traffic signal controller cabinet, where a receiver ports the data to the small EWS field-hardened microprocessor computer that contains the other EWS subsystems. The TDR sensor was recently developed for a different train application as part of a Transportation Research Board (TRB) program for a different train application. It is undergoing field-testing and shows promise, but is as yet unproven for this application. The TDR unit induces an electrical pulse into the rails that travels outward until it encounters the wheels of an approaching train. A portion of the pulse is then reflected 3
back; the reflected pulse can be analyzed to provide the train's speed and distance. The TDR detector would be located at the crossing itself, and the data transmitted to the nearby traffic signal controller via hardwire or wireless. The EWS prediction subsystem uses an algorithm to predict the arrival time of the train and its passing duration based on the sensor data. Others have successfully used a simple algorithm, assuming a fixed speed. A fixed speed assumption is valid because the railroad companies strictly enforce train speed limits. The EWS congestion mitigation subsystem is the core of the research and it potentially could decide to take different actions, ranging from using different EWS parameters to aborting the use of the system because of uncertainty for that particular train. The model tested different parameters using an EWS algorithm developed for the study. The algorithm was written in the model's macro language, which required a significant effort to develop and refine. In addition, a third-party expert also was used to review the completed algorithm, which confirmed the accuracy of its logic and code. The algorithm does not impact the safety of the current, time-tested train premption control scheme. The algorithm always aborts when a train preemption signal is received. This is the same method currently used by NEMA-compliant traffic signal controllers to preempt the normal control sequence when a train arrives. The algorithm is designed to finish all of its operations just as the train preemption signal is received. However, even if it is not finished, the algorithm will always abort when the train preemption signal is received. Before/After Study Results Three measures-of-effectiveness (MOEs) were selected for evaluating the effects of the EWS: (1) delay, (2) travel time, and (3) queues. Of these, delay was the primary reporting MOE. Because of the tee intersection geometrics, two intersection movements (parameters) were available for receiving additional green time before the train arrived: (1) WB LT, which concurrently times WB TH and NB RT and (2) NB LT and NB RT, which time concurrently. The conflicting movements are WB LT, NB LT, and NB RT. Examining these two parameters while varying the other important factors of vehicle traffic flows, train traffic flows, MOE duration period, and train prediction errors, created substantially more cases than resources could accommodate. Therefore, only five cases were selected for testing the EWS. Two to six scenarios were modeled and tested for each case as well as the "no improvements" (before) scenario. Five major variables were studied by comparing results from the five cases and their multiple scenarios. Crossing gates downtime was varied at three levels: 4.5, 2.6, and 1.5 minutes, based on site train data. MOE results were analyzed at two levels: 15- and 30minute durations. Conflicting movement vehicle traffic was varied at three levels: actual, twice actual, and three times actual volume. The impact of train arrival prediction error was investigated at three arrival times: 25 seconds early, on-time, and 25 seconds late. Lastly, the impact of the parameters on the queue lengths was examined. From the perspective of the entire intersection, the overarching before/after results for this site are that the "costs" of the EWS outweigh the "benefits" when intersection delay is considered. The benefits are the savings in delay to the conflicting movements that 4
receive additional green time, while the costs are the increase in delay to the nonconflicting movements that are the donors of additional green time. Hardware-in-the-Loop Testing To test the EWS algorithm, a hardware-in-the-loop technique was used with a NEMA controller. This technique linked an actual NEMA controller containing the EWS algorithm to the traffic simulation model. The algorithm was implemented by linking four of the controller's built-in preemptors. The results verified that a microcomputer inside a traffic signal cabinet could send a signal to a standard NEMA controller that would then initiate the appropriate EWS algorithm routine. Conclusions and Recommendations Four generalizations appear to be supported by the study results, but more studies at other sites are needed to conclusively verify or dispute them. The first generalization is that the effectiveness of the Early Warning System is highly dependent on the site geometry, and on the vehicle and train traffic volumes. The relative volumes of individual intersection movements are critical because when a conflicting movement is given "extra" green time by the EWS before the arrival of a train, it "steals" that time from other movements. This complex, dynamic interplay is site dependent. The second generalization is that vehicles must be available to use the "extra" green time before the train arrives. This may not occur unless there were cycle failures before the train arrives. Without these cycle failures, there may not be enough vehicles in or nearing the queue to use the "extra" green time, especially when the "extra" green time is lengthy. The third generalization is that reducing long queue lengths for safety purposes may justify an increase in overall intersection delay. This may be especially true if the long queues are backing-up into nearby intersections or onto freeways. The fourth generalization is that the EWS may also be used in other ways to reduce congestion. One example is to send a warning signal to a DMS (dynamic message sign) that alerts drivers of a train's imminent arrival at the crossing so that they can take an alternate route. In conclusion, the EWS was ineffective for the study site, but two traffic characteristics may be confounding the results: (1) insufficient pre-train queue lengths for conflicting movements that limit their ability to utilize the "extra" green time; and (2) the lack of a single dominant conflicting flow at the intersection (the study site had fairly balanced cross-flows). Based on these lessons, a follow-up study is recommended at a new site with favorable geometry and traffic volumes. A multi-phase, incremental study approach should be used that allows termination of the study at the end of any phase that has clearly unfavorable results.
5
(blank)
6
1.
INTRODUCTION
1.1. MOTIVATION FOR RESEARCH Arizona's primary railroad system developed along the most accessible and constructible route alignments in advance of its primary highway system. Therefore, when a highway was developed, it was often placed parallel to the existing railroad tracks. The outlying suburban areas in Arizona use the primary highway system for trips to the urban areas for work, school, shopping, and recreation. The rapid growth of the urban areas in Arizona has caused suburban housing areas to be developed outward along highways leading into the urban areas. Where such highways are parallel to a railroad line, daily commuters on one side of the highway must cross these tracks to reach the highway. The highway is often the primary, and in some cases the only, route available to these commuters to reach the urban areas. These commuter at-grade crossings are typically the crossing of the railroad by the feeder road from the housing area to the highway, which may be a two-way, two-lane (TWTL) highway or a four- or more lane, limited access freeway. As the suburban area fills in, the feeder road--which usually begins as a TWTL road-may be upgraded to more lanes and become surrounded with commercial development. In the absence of a flyover structure (a roadway over- or underpass), the problems associated with at-grade crossings remain, and they typically will get worse as the volumes of vehicle and train traffic continue to increase. These commuter at-grade crossings cause congestion problems when the volume of traffic crossing the tracks is sufficiently large and/or the frequency of trains is sufficiently high. This is already occurring at various sites in Arizona and is destined to spread to more sites statewide. Continued growth in train traffic is predicted by the railroads and as Arizona's population continues to increase1, statewide vehicular traffic is also predicted to increase. Arizona's population is projected by the U.S. Census Bureau to
1
Arizona's statewide population has grown from approximately 1,300,000 in 1960 to 5,100,000 in 2000. The rates of growth each decade beginning with the 1960s through the 1990s are respectively 36%, 53%, 35%, and 40% per decade. During the same 40-year span, the PhoenixMesa metro area grew from approximately 725,000 to 3,250,000 and had rates of growth over the four decades of 43%, 54%, 40%, and 45% per decade. Tucson metro area grew from approximately 265,000 in 1960 to 845,000 in 2000 and had rates of growth from the 1960s through the 1990s of 32%, 51%, 25%, and 37%. Yuma metro's growth over this 40-year span was from approximately 46,000 to 160,000 and by decade, the growth rates were 32%, 49%, 18%, and 50% per decade. The Flagstaff metro area grew from approximately 45,000 in 1960 to 122,000 in 2000 and had rates of growth from the 1960s through the 1990s of 14%, 56%, 29%, and 20%. Nationwide from 1990 to 2000, Arizona ranked number 2, behind Nevada, as the fastest growing state by percent population growth. During this same period, Phoenix-Mesa metro area ranked as the 8th top metro growth area by percentage, Tucson ranked 37th, Yuma ranked 3rd, and Flagstaff ranked 69th (CensusScope 2000). Yavapai County, which includes the Prescott valley cities, had population growth from approximately 30,000 in 1960 to 170,000 in 2000 and experienced decade-by-decade growth rates of 27%, 86%, 58%, and 55% per decade over this 40-year span (Arizona Quicklinks 2005).
7
double from 2000 to 2030 from approximately 5.1 million to 10.7 million (State Interim Population Projections 2005). ADOT currently has 30 traffic signals on the state highway system that incorporate train preemption. Off the state system, the urban areas in Arizona maintain and control a significantly larger number of such traffic signals. Many of these operate under similar high vehicle and/or train traffic conditions, causing congestion problems. Additionally, these types of at-grade crossings cause safety problems when the roadway that crosses the railroad leads to/from a nearby signalized roadway intersection. This is usually the case. This specific type of at-grade crossing--the commuter at-grade crossing--is the focus of this research. The congestion and safety problems caused by these commuter at-grade crossings arise from a series of conditions that are briefly listed below and discussed in more detail later in this report. 1. When the roadway crossing the railroad leads to/from a nearby signalized roadway intersection, the right-of-way control systems for the railroad crossing and the roadway intersection act independently. These two control systems can act at cross-purposes to each other, causing safety problems. 2. The organizational and operating systems of the railroad company and the agency operating the traffic signals have evolved over time and resist change for safety and liability reasons. There currently is no technical or jurisdictional option available for the interactive management of the rights-of-way between the atgrade crossing and the roadway intersection. 3. The current method to mitigate the safety problems is for the railroad company to send a signal to the roadway agency when a train is approaching the crossing and another signal once the train has cleared the crossing. The roadway agency uses these signals to independently address the safety problems by altering its intersection control scheme in a manner known as train preemption (or simply preemption). 4. The current signalized roadway intersection train preemption control scheme's primary purpose is safety; congestion mitigation is a secondary goal. Congestion mitigation occurs only after the train has passed, in a reactive mode; none occurs in a proactive mode before the train arrives. 5. When the volumes of vehicles crossing the tracks are sufficiently large and/or when the duration and/or frequency of the passing trains is sufficiently high, the signalized intersection preemption traffic control scheme is insufficient to clear all of the vehicles. Therefore, the preemption control scheme delays the clearing of the congestion caused by a train passing for some period of time. 6. This delay in clearing the congestion, if sufficiently long, causes operational problems for the roadway system. Depending on the geometrics involved, when congestion is sufficient, queues of vehicles can back up long distances. The nearby intersection preemption control scheme reduces the possibility of these queues backing up into it. But other intersections, upstream and downstream from the nearby intersection and the railroad crossing, can experience queues backing up into them, causing safety problems. 8
The safety and congestion problems arising from these commuter at-grade highwayrailroad crossings are the focus of the research in this report and give rise to the research question that was investigated. 1.2. SCOPE OF THIS RESEARCH The primary objective of this study is to investigate these central issues: Research Question: Can solutions be applied at a signalized intersection, before a train passes a nearby at-grade highway-railroad crossing, that will mitigate the congestion that will occur after the train has passed? Furthermore, can this be accomplished using a standard traffic signal controller? In order to accomplish this, an initial research workplan was developed and approved by the project's Technical Advisory Committee (TAC). This workplan was modified during the progress of the research as guided by the unfolding results and unforeseen challenges encountered. The TAC also approved these modifications as they occurred. The final research workplan consisted of the following major tasks: 1. Review work by others that may be useful to this research. 2. Acquire major research equipment and modeling software needed to accomplish the work and train the research staff in its use. 3. Collect geometrics and traffic data at the selected study site. 4. Investigate a site-specific train arrival/prediction model. 5. Develop a microscopic traffic simulation model for the study site. 6. Develop an Early Warning System algorithm to apply congestion mitigation solutions before the train arrives. 7. Using the microscopic traffic simulation model and the EWS algorithm, test the research question using a series of variables and evaluate the results using a series of Measures of Effectiveness. 8. Using hardware-in-the-loop techniques, demonstrate the ability to implement the EWS algorithm using a standard NEMA traffic controller. The project was formally initiated in March 2003. The initial meeting with the project sponsors and technical advisors was held on May 1, 2003, at ADOT's district office in Flagstaff. The research was actively guided by a Technical Advisory Committee whose members are listed in Table 1. 1.3. ORGANIZATION OF THE REPORT The report is organized into chapters. Each chapter reports on an element of the research work. If additional detail is deemed relevant, it is included in an Appendix. The organization scheme for chapter topics and location focuses on understanding the outcomes rather than the chronological flow of work.
9
Table 1: Project 557: Technical Advisory Committee Members Ken Cooper Sam Elters Chuck Gillick John Harper Mike Lessard Ann Phillips George Wendt Tim Wolfe Gerry Craig Steven Hill David Wessel Dennis Roberts Debbie Casson ADOT, Roadway Standards ADOT, Kingman District Engineer ADOT, Northern Region Traffic Engineer ADOT, Flagstaff District Engineer ADOT, Traffic Engineering Group ADOT, Traffic Engineering Group ADOT, Office of Risk Management ADOT, Transportation Technology Group City of Flagstaff, Traffic Engineer City of Flagstaff, Traffic Signals Flagstaff Metropolitan Planning Organization City of Kingman, Community Development City of Kingman, Engineering Department
Mike McCallister BNSF Railway Company Dan Owsley Alan Hansen BNSF Railway Company Federal Highway Administration
As is typical with most research, many unanticipated challenges were encountered that were not envisioned in the workplan. However, unless these have a direct bearing on the results, they are not reported here. A detailed Table of Contents is given to assist the reader in finding topics of interest.
10
2.
PROBLEMS WITH AT-GRADE HIGHWAY-RAILROAD CROSSINGS
An at-grade highway-railroad crossing is one where a highway and railroad intersect on the same plane or grade. This is often simply termed as an "at-grade railroad crossing." A grade-separated crossing is one where a structure physically separates the two routes, either by the railroad going over the highway or the highway going over the railroad. An at-grade crossing causes a right-of-way conflict between the highway vehicular traffic and the railroad train traffic. This conflict is similar in concept to a regular intersection between two highways. Where two highways intersect, highway traffic control devices handle the right-of-way control: yield signs, stop signs, or traffic signals. Because a train requires a long distance and time to stop, vehicle traffic is always required to yield rightof-way at an at-grade railroad crossing to a passing train. An analogy using a typical intersection between two roads would be that the railroad acts as the mainline, which always has the right-of-way, and the highway acts as the side road, which has stop control. Stop control at a railroad crossing can be passive or active. Passive stop control is often the familiar "crossbuck" at the side of the road just before the track crossing plus various additional railroad crossing signs. Often, a typical highway stop or yield sign may also be present. Active stop control usually consists of flashing lights, or flashing lights with gates. In both passive and active control, the vehicular traffic is required to stop and the train is given the right-of-way. Typically, high volumes of vehicular traffic and/or train traffic at an at-grade railroad crossing dictates active stop control using flashing lights with gates. The first conceptual problem to arise at active control types of crossings is the split jurisdiction within the crossing. All of the railroad control is the jurisdiction of the railway company and all of the highway control is the jurisdiction of the governmental agency that owns the highway. Neither control system relinquishes control to the other system, so there is no technical or jurisdictional option available for an interactive management of the right-of-way at the crossing. What has evolved over time is a set of guidelines adopted by both groups' industry associations for active crossings. The basic conceptual methodology is that the railroad company's control system will send a signal to the highway agency's control system when a train is approaching the crossing and another signal once the train has cleared the crossing. 2.1. TRAIN SAFETY When a vehicle and a train collide, almost invariably the vehicle driver and occupants are injured, often fatally. The train engineer (driver) and train occupants are typically not injured due simply to the physics of the disparity in the mass of the two objects, although there are exceptions. Often, however, the train engineer is emotionally impacted and may be incapable of driving a train again. Typically a train cannot stop within sight distance of an at-grade crossing even when it locks its brakes. This means that when a train engineer first sees a vehicle stalled on the tracks and immediately hits the train brakes (and lays on the whistle), the engineer knows the he will not be able to stop in time but 11
has to watch as the fully-braking train approaches and then collides with the vehicle, finally coming to a complete stop at a considerable distance beyond the crossing. In addition to the emotional and possible physical injuries of train personnel, the train traffic on that track and possibly adjacent tracks is halted for a considerable period of time to clear and investigate the collision. Railroads often have little if any ability to route train traffic around the collision site causing all train traffic to come to a halt. The economic impacts of such disruptions on the railroad operations can be large. The railroad companies have vigorously promoted grade-separated crossings, active atgrade crossing control, and reduced numbers of at-grade crossings with passive control1. These efforts, aided by the governmental roadway jurisdictions involved, have helped to significantly reduced the number of at-grade crossing collisions over the last several years. For example, between 1990 and 2000, the national number of highway-railroad incidents decreased from 5,715 to 3,502 and the incident rate per million train-miles decreased from 9.39 to 4.84 (Federal Railroad Administration 2001). Additionally, the railroad companies have improved their active at-grade crossing control systems. The older, but still primary, method used by the railroad companies to gauge when to send a signal to the highway authority indicating that a train is approaching is to locate a sensor on the tracks at a fixed distance from the crossing. One drawback of this method is that the time between when the signal is sent and when the train reaches the crossing varies depending on the speed of the train. This is mostly mitigated because the railroads use strictly enforced train speed limits, however the train can go at a slower speed than the limit. The newer, improved method used by the railroads at some crossings provides the signal at a fixed amount of time before the train reaches the crossing, regardless of train speed. 2.2. VEHICLE SAFETY The right-of-way control system at the at-grade railroad crossing is installed and operated by the railroad company. At a passive control crossing, the signage is the only right-ofway control system although the train engineer uses his whistle to sound a warning as he approaches a crossing2. Additional signage may also be placed at the crossing by the authority that owns the roadway and/or the railroad company.
1
BNSF announced that in December 2003, it closed its 2,000th highway-rail grade crossing since the beginning of year 2000. During the four-year period from 2000 to 2003, BNSF closed six percent of its grade crossings, in a cooperative effort with landowners and communities along its route to identify unnecessary or redundant grade crossings. BNSF currently has approximately 30,000 at-grade crossings across its 32,500-mile rail network (BNSF Press Release 2004). In response to a legislative mandate, FRA has issued a Final Rule on the Use of Locomotive Horns at Highway-Rail Grade Crossings, which requires that locomotive horns be sounded as a warning to highway users at public highway-rail crossings. It takes effect on June 24, 2005; before that, the sounding of horns at public crossings was subject to applicable State laws and railroad rules. The final rule provides an opportunity, not available until now, for thousands of localities nationwide to mitigate the effects of train horn noise by establishing new "quiet zones." The rule also details actions communities with pre-existing "whistle bans" can take to preserve them (Federal Railroad Administration 2005-1).
2
12
At active control at-grade crossings, the railroad company is responsible for sensing the approaching train, activating the flashing lights (and gates, if applicable) in sufficient time to notify vehicle traffic not to enter the railroad crossing area until the train has passed. Once the train has passed, the railroad company is responsible for stopping the active warning system devices, which allows the vehicles to cross the railroad crossing. Typically an active at-grade railroad crossing control system is located in an urban area where the railroad is crossing through the urban area's roadway network. In this situation, active control systems are placed at those at-grade crossings that carry high vehicle and/or train traffic. Often the vehicle roadway crossing the railroad leads to/from a nearby intersection of two roadways. When the volume of vehicle traffic at this nearby intersection is sufficiently high, the intersection right-of-way will be controlled by a vehicle traffic signal control system. This traffic signal control system apportions the right-of-way to vehicles by giving each individual movement the right-of-way (green light) in rotation through a cycle, while simultaneously withholding the right-of-way from the other conflicting movements (red light). Therefore, a driver knows he has the right-of-way when he gets the green light and can safely proceed across the intersection. Problems arise when a roadway intersection is located near an at-grade railroad crossing because the railroad crossing control system and the roadway intersection control system act independently. An integrated control scheme cannot be used because neither of the two jurisdictions involved relinquishes control to the other. This causes two primary problems. The first is that when sufficient vehicles are waiting to get the green light on the roadway that crosses the railroad and leads to the roadway intersection, the queue that forms will back up across the at-grade railroad crossing. If a train approaches, these vehicles cannot move until they get the green light at the roadway intersection. The second problem is that while the train is passing, the roadway intersection traffic signal system continues to give vehicles the right-of-way to pass through the intersection toward the at-grade railroad crossing. When sufficient vehicles have done this the queue waiting at the at-grade crossing backs up into the roadway intersection. The method used to mitigate these problems is for the railroad company to send a signal to the roadway agency when a train is approaching the crossing and another signal once the train has cleared the crossing (Federal Highway Administration 2003). The roadway agency uses these signals as inputs to its roadway intersection traffic control scheme to trigger a special control scheme called preemption. Conceptually, once the signal of an approaching train is received, the normal rotation of the intersection right-of-way apportionment is interrupted (preempted) and vehicles that may be queued across the atgrade railroad crossing are given the green light to allow them to immediately clear the crossing. Then while the train is passing, the rotation of intersection right-of-way skips those movements that would allow vehicles to approach the train crossing, thereby reducing the likelihood of a queue backing up from the crossing into the intersection. When the signal is received that the train has passed, the right-of-way is first given to a designated movement(s) and then the intersection control scheme is returned to its normal rotation scheme of apportioning the right-of-way. Typically these designated movements are those that were skipped while the train was passing.
13
2.3. VEHICLE CONGESTION The roadway intersection located near an at-grade railroad crossing operates under the preemption traffic control scheme in response to the signals it receives from the railway company signaling the approach of a train and later the leaving of the crossing by the train. Once the signal is received that a train is approaching, the sole purpose of the preemption control scheme, both before the train arrives and as it passes, is the safety of the vehicles that might be placed in danger if the traffic control system was not aware of the approaching train. Once the signal is received that the train has cleared the at-grade crossing, the preemption traffic control scheme addresses the congestion that was caused by the train passing. The typical method is to give the right-of-way to those movements that wanted to cross the tracks, but were blocked from doing so while the train was passing. This scheme works reasonably well to clear the congestion caused by the passing train if the volumes of vehicles that are queued waiting for the train to pass are not too large. However, when these volumes are very large and/or when the frequency of the passing trains is very high, the preemption traffic control scheme is insufficient to clear these large volumes of vehicles. Therefore, the preemption control scheme delays for some period of time the clearing of the congestion caused by the train passing. This delay, if sufficiently long, causes operational problems for the roadway system that the roadway jurisdiction(s) try to address in various ways. Depending on the geometrics involved, when congestion is sufficient, queues of vehicles can back up long distances. The nearby intersection preemption control scheme reduces the possibility of these queues backing up into it. But other intersections, upstream and downstream from the nearby intersection and the railroad crossing, can experience queues backing up into them causing severe safety problems. One way to address these safety and congestion problems is to eliminate the at-grade crossing by creating a grade-separated crossing, also called a "flyover." Often this is the preferred method but this solution is very expensive. Additionally, when the railroad is crossing several roadways in an urban roadway network several flyovers may be required. In this situation an area-wide scheme is preferred. This scheme typically designates two or more railroad crossings for flyovers and closes the other crossings.
14
3.
SITE SELECTION, GEOMETRICS, AND TRAFFIC
3.1. SELECTION OF THE STUDY SITE The investigation of the research question required the selection of an actual site that was experiencing the requisite conditions. Recall that commuter at-grade crossings are defined as having these characteristics: 1. A roadway and railroad intersect on the same plane or grade. 2. The roadway crossing the railroad leads to/from a nearby signalized roadway intersection. 3. Traffic crossing the at-grade highway-railroad crossing have one or more of these characteristics that occur more-or-less concurrently for recurring periods during a year, typically during weekday vehicle AM and/or PM peak periods: a. Vehicle traffic volume is large. b. Train frequency is high. c. Duration the crossing is closed to allow a train(s) to pass is long; this is a function of train length, speed, number of tracks, and frequency of trains. The term "commuter" is applied to the term "commuter at-grade crossings" because usually the high volume of vehicle traffic is primarily attributed to drivers making hometo-work trips or work-to-home trips. Traffic engineers call these the AM peak period and the PM peak period. Another requirement for a study site was that it be within the jurisdiction of the Arizona Department of Transportation (ADOT). This meant that a state highway had to be crossed at-grade by the railroad (atypical) and/or that the highway was part of the nearby signalized intersection (typical). The potential study site location was further refined when a secondary sponsor for the research joined the study, the City of Flagstaff. One potential site that satisfied both ADOT and the City was the intersection of Route 66 and Enterprise Road. The north-south leg of this intersection (Enterprise) was crossed at-grade by the Burlington Northern and Santa Fe (BNSF) Railway's double mainline tracks. The Enterprise Road crossing is located approximately 75 feet south of the intersection. Additionally, the BNSF also has parallel spur and siding tracks at this crossing for a total of 4 tracks, however the train traffic of interest all occurs on the double-track mainline (see Figure 1). 3.1.1. Railroad Equipment and Operations Used at the Site "The Federal Railroad Administration was created by the Department of Transportation Act of 1966 (49 U.S.C. 103, Section 3(e)(1)). The purpose of FRA is to: promulgate and enforce rail safety regulations; administer railroad assistance programs; conduct research and development in support of improved railroad safety and national rail transportation policy; provide for the rehabilitation of Northeast Corridor rail passenger service; and consolidate government support of rail transportation activities." (Federal Railroad Administration 2005-2)
15
The Secretary of the Department of Transportation has authority over both the Federal Railroad Administration and the Federal Highway Administration (FHWA), the two primary regulatory groups over railroads and highways. State Law governs highwayrailroad crossings but typically a State adopts the standards, with modifications to fit state needs, as codified in the Manual on Uniform Traffic Control Devices (MUTCD - Federal Highway Administration 2003). Arizona has adopted the MUTCD, with modification, but none of the modifications significantly alter the standards in the MUTCD that govern at-grade crossings.
Figure 1: Aerial Photos Of The Study Site The left photo shows the area surrounding the study site. The study site includes the atgrade crossing of Enterprise Road with the BNSF tracks, and the Route 66/Enterprise "Tee" intersection just to the north of the at-grade crossing. Route 66 and the BNSF Railroad mainline tracks run parallel. The photo at right is a close-up of the study site. Railway companies own and maintain the tracks, and generally own the property (rightsof-way) to either side of the tracks. At at-grade crossings, they generally install and maintain the tracks, the roadway surface between and around the rails, and traffic control devices on their rights-of-way. While the railway owns the track, the roadway at a crossing is typically owned by a government agency. This roadway agency maintains the road approaching the crossing on either side of tracks. The Federal Highway Administration is responsible for public grade crossing issues that affect highway safety. FHWA, through the MUTCD, provides guidelines and standards 16
for the correct design of grade crossings, the assessment of safety at a grade crossing, and appropriate placement of traffic control devices at and on the approach to a grade crossing. These traffic control devices at the study site include circular advance warning signs, crossbucks (the familiar X-shaped signs), pavement markings, and bells, gates, and flashing lights as shown in Figure 2 (Federal Railroad Administration-3, 2005).
Figure 2: Photo Of The At-Grade Crossing At The Study Site Study site looking south from the Route 66 and EnterpriseRd.intersection to the at-grade highway-railroad crossing. The northbound vehicles on Enterprise Rd., facing the viewer, and the lone southbound vehicle are waiting behind lowered gates as a train passes. All of the red lights on the gates, crossbucks, and overhead gantries are flashing. Since both the railway company and the roadway agency maintain jurisdiction and responsibility for safety in their own rights-of-way, an at-grade crossing represents the unique condition wherein both have some responsibilities for a common portion of land. Technically, however, the land at the crossing is owned by the railway company and at an active control crossing, they manage and operate the control system and appurtenances involving the crossing itself. This control system is complex and must be compatible with the control systems that the railway company uses to manage its facilities and dayto-day operations up and down the line (see Figure 3). For purposes of this report, it is sufficient to conceptually describe the railway's control system at the crossing and include only those parts that affect the vehicles operating on the roadway. At the study site, the BNSF Railway Company is responsible for sensing the approaching train and activating the flashing lights and gates in sufficient time to notify vehicle traffic not to enter the railroad crossing area until the train has passed. Once the train has passed, BNSF is responsible for stopping the active warning system devices, which allows the vehicles to cross the railroad crossing.
17
Figure 3: Photo Of At-Grade Crossing Equipment At The Study Site Looking east across the at-grade crossing showing the primary active crossing gates and warning lights. The nearside vehicle has just exited the Route 66 and Enterprise Rd. intersection and is heading southbound on Enterprise Rd. The far vehicle is heading northbound toward the intersection. ADOT manages and operates the control system of the Route 66 and Enterprise Road intersection that lies approximately 75 feet north of the at-grade crossing. Neither the BNSF at-grade control system nor the ADOT signalized intersection control system relinquishes control of its system to the other during the passing of a train. They operate independently, which precludes a joint, interactive control scheme. In order to allow the intersection control system to modify its control scheme during the passing of a train, the standard method (Federal Highway Administration 2003) used nationally is for the railway company to notify the roadway agency. Conceptually the railway crossing system notifies the intersection control system by sending a signal to the roadway agency 18
when a train is approaching the crossing and another signal once the train has cleared the crossing1. At the study site, BNSF operates an advanced type of detection system. This system can provide a signal at a constant time interval before the train arrives rather than at a constant distance from the crossing. ADOT and BNSF have agreed on this constant notification time interval. The constant time interval has a small variance but during an intensive data collection period at the site, the predicted time to crossing was typically within +/- 1 second2. The BNSF detection system calculates the speed of the train and predicts the time of arrival at the crossing. It waits until the constant notification time interval remains and then sends the signal to ADOT. ADOT uses this signal to interrupt its normal operation of the traffic control signal to transfer control to a special control mode of operation called preemption. During preemption, the normal sequence of traffic control signal indications are interrupted to avoid entrapment of vehicles on the highway-rail grade crossing by conflicting aspects of the intersection traffic control signals and the highway-rail grade crossing flashing-light signals and gates. 3.1.2. Traffic Signal Equipment and Operations Used at the Site ADOT manages and operates its intersection traffic control signals in accordance with the MUTCD, as modified for the State of Arizona, including its preemption control mode for at-grade crossings (Traffic Group 2005). At the study site, ADOT uses a NEMA controller3 and cabinet.
1
The MUTCD specifies a fail-safe type of communications method from the railroad control system to the roadway intersection control system. The preemption feature shall have an electrical circuit of the closed-circuit principle, or a supervised communication circuit between the control circuits of the highway-rail grade crossing warning system and the traffic control signal controller. The traffic control signal controller preemptor shall be activated via the supervised communication circuit or the electrical circuit that is normally energized by the control circuits of the highway-rail grade crossing warning system. The approach of a train to a highway-rail atgrade crossing shall de-energize the electrical circuit or activate the supervised communication circuit, which in turn shall activate the traffic control signal controller preemptor. This shall establish and maintain the preemption condition during the time the highway-rail at-grade crossing warning system is activated, except that when crossing gates exist, the preemption condition shall be maintained until the crossing gates are energized to start their upward movement. When multiple or successive preemptions occur, train activation shall receive first priority. (Federal Highway Administration 2003) BNSF gathered information continuously from its crossing equipment recording devices at the study site in support of this study for a 7-day period from 4/26/04 to 5/3/04. At the study site intersection, ADOT uses a NEMA Econolite ASC/2S-2100 controller (Econolite Control Products, Inc. 2005). This is a TS2, Type 2 controller operating in the TS1 environment in a Type 1 Cabinet. ADOT uses an extra Econolite board within the controller to handle its preemption communications and uses the D Plug for all input and output preemptor calls.
2
3
19
ADOT's typical practice for its preemption mode is used at the study site and conceptually consists of the following sequence of events. Specifics given all refer to the study site4: 1. Receive the preemption signal from the railroad (BNSF) that indicates the train is approaching the site. 2. Immediately go to the Preemption Track Clearance (TC) Phases (NB LT and NB RT at the study site). a. The designated Preemption TC Phases under ADOT's typical procedures are those movements that potentially can be queued up across the railroad tracks waiting for a green light. (At the study site, these are the NB LT and NB RT movements. Since the intersection is a "tee" intersection, there is no SB leg, which means there are no NB TH, WB RT, or EB LT movements and, of course, no SB movements of any kind.) b. If the green is timing a movement(s) other than the Preemption TC Phases when the preemption signal is received, then this movement(s) will be ended. It will be ended in a safe manner, which means that it will be given a designated preemption minimum amount of green (5 seconds at the study site), followed by a yellow (change interval) and an all-red (clearance interval). These yellow and all-red intervals can be designated specifically for preemption or they can be allowed to default to those used during normal operations (yellow and all-red times used in normal operations are used at the study site). If the minimum amount of green has already elapsed when the preemption signal is received, the movement(s) will immediately proceed to its yellow and all-red. c. If the green is already timing for the movement(s) designated as the Preemption TC Phases, then this movement(s) will continue for the designated length of TC Green time interval, which commences when the preemption signal is received. d. Once the Preemption TC Phases have started timing their green, they will continue in green until the designated TC Green time interval has elapsed. e. Once the TC Green time interval has elapsed, a yellow and an all-red interval will follow. These intervals can be designated as the TC Yellow and TC All-Red intervals or they can be allowed to default to those used
4
The nomenclature used throughout this report describing the movements of traffic through an intersection are from the perspective of the direction of traffic. For example, a vehicle that is on the south side of an intersection and traveling north toward the intersection is a NB (northbound) vehicle. This is further refined by designating the direction the vehicle intends to go after it leaves the intersection, e.g., NB LT (northbound left-turn), which could also be called NB to WB (northbound to westbound). In this report, the NB LT type of designation is used. So when a group of vehicles are described as NB, the group includes all vehicles that intend to go NB LT, NB TH (northbound through) and NB RT (northbound right-turn). Similar terms are used for WB (westbound), SB (southbound), and EB (eastbound).
20
during normal operations (the yellow and all-red times used in normal operations are used at the study site). 3. Go to Preemption Hold Phases (WB TH and EB TH at the study site). These are phases that do not conflict with the passing train. Train conflicting phases are those that would direct vehicles toward the at-grade railroad crossing or away from it while the train is passing (WB LT, EB RT, NB LT, and NB RT at the study site). If any of the Preemption Hold Phases need to be run separately from each other, they will be run in their normal operations sequence, while omitting the train conflicting phases from the sequence. (At the study site the Preemption Hold Phases (WB TH and EB TH) do not conflict with each other so they run simultaneously.) This will continue until the railroad (BNSF) sends the signal indicating the train has left the crossing. a. To insure safe operations, a Minimum Hold Time is designated. This minimum time must be satisfied in addition to receiving the signal from the railroad that the train has left the crossing before control can proceed to the Preemption Exit Phases. 4. Go to Preemption Exit Phases (NB LT and NB RT at the study site) and return to normal operations. Since the signal has returned to its normal operations, these Preemption Exit Phases time their green, yellow, and all-red intervals using their normal operations intervals. a. Preemption Calls are also placed on any movement(s) desired (WB LT and WB TH at the study site) as control is returned to normal operations. The normal sequence of movements used in normal operation is observed so the movement(s) that is normally called after the Preemption Exit Phases has finished is what runs next. What the Preemption Calls do is to ensure that the movements that were called will be serviced even if they don't have any vehicles waiting. (For the study site, the normal sequence serves the WB LT and WB TH movements (the Preemption Exit Calls at the study site) after the NB LT and NB RT movements (the Preemption Exit Phases at the site) have run.) The signal heads are located on overhead cantilevered arms and on the uprights to these arms. There are also two pedestrian crossings: east-west on the south side of the intersection and north-south on the east side of the intersection. These have low pedestrian traffic (see Figure 4).
21
Figure 4: Photo Of The Intersection At The Study Site Looking south at the study intersection, which is a "Tee," the missing leg being on the north side, from where the photo is taken. The intersection signal lights are controlled with a NEMA controller, and signal heads are mounted on side and overhead poles. Route 66 is the east-west roadway running left-to-right in the foreground of the photo. The at-grade railroad crossing can be seen in the background, crossing Enterprise Road.
3.2. SITE GEOMETRICS AND MODIFICATIONS FOR MODEL 3.2.1. Current Geometrics at the Study Site The study site is the intersection of Route 66 and Enterprise Road in Flagstaff, Arizona. The intersection serves both commuters and tourists as well as commercial vehicular traffic. Although the intersection has four legs, the fourth leg on the north side of the intersection is a driveway into a vacant city-owned lot. There are no traffic signal heads servicing this leg, i.e., SB traffic. Therefore, the intersection is functionally a Tee intersection. This intersection was significantly improved to its current configuration approximately three years before the study began. The other three legs service significant volumes of vehicular traffic. The EB and WB movements are on Route 66. The normal cross section for Route 66 is five lanes, with two through lanes in each direction and a center common left-turn lane. Both EB and WB directions have two lanes for through movements. EB has a single right turn lane and a long storage lane. WB direction has a single dedicated left turn lane that is essentially of unlimited length due to the center common left-turn lane. Both the WB LT and the EB RT movements lead traffic into Enterprise Road and across the railroad tracks, which are located approximately 75 feet south of the intersection. Enterprise Road is a north-south connector road that services traffic between the study intersection and the intersection of Butler Avenue and Huntington Road, which lies approximately 800 feet to the south. NB Enterprise Road begins at the intersection of Butler Avenue and Huntington Drive as two lanes. A merging single slip lane from Huntington Drive quickly joins it. As it approaches the study intersection, it widens into a four-lane section containing dual left turn (LT) lanes, a hatched auxiliary lane and one right turn (RT) lane. The dual LT lanes lead vehicles into westbound (WB) Route 66 while the RT lane leads into eastbound Route 66. The southbound Enterprise movement 22
leaves the study intersection with two lanes. There is approximately a 60-foot storage length between the northbound (NB) stop bar and the railroad crossing. Route 66 and Enterprise Road have sidewalks on both sides but pedestrian traffic is low. Pedestrian crossings at the study intersection are limited to two: a north-south crossing on the east side and an east-west crossing on the south side. 3.2.2. Modified Tee Intersection Geometrics Used for the Study The study intersection had significant congestion problems before it was improved in 2002-2003. These problems were substantially reduced by the geometric improvements. Additionally, the close coupling of the two intersections at each end of the Enterprise Road connector caused them to interact with each other, although the timing of their signals is not coordinated. Substantial efforts were spent modeling the current configuration of the two closecoupled intersections. The modeling software used in the study is VISSIM, which is described in detail in Chapter 4. Models were developed using current vehicle traffic through these intersections. The Early Warning System was initially tested using this configuration. Significant problems developed because of the complexities that occur at the site. It was discovered that while this site qualified as a commuter at-grade crossing, its complexity made it difficult for these reasons: The geometric improvements to Route 66/Enterprise Road had already reduced a significant portion of the congestion the EWS was designed to alleviate. The close coupling of the two intersections caused an interaction that was most probably confounding results. The site was atypical of the site the EWS was designed to help. A typical site would have a feeder road leading across an at-grade crossing to join a main highway. The traffic on the feeder road would be to/from an isolated residential area. The study site consists of two arterials, Route 66 and Butler Avenue, that parallel the railroad tracks on either side. These are cross-connected infrequently, but when they are, significant traffic is exchanged between them. This causes the study intersection to have strong movements in several directions rather than the anticipated primary strong movement to/from a residential area with AM and PM peaks. It was agreed with the project TAC to attempt to overcome some of these difficulties by modeling a modification of the study site. This modification was used for all testing and results, except traffic volumes were modified in some test cases as described later. Therefore, the modeled study site had these characteristics: 1. Pre-improvement geometrics: The intersection and at-grade crossing geometrics were modeled using the pre-improvement geometrics. The only improvement on the east-west Route 66 route was to the EB RT storage lane, which was shortened to 360 feet. Enterprise Road had several changes that reduced the cross section at the intersection to one SB lane and two NB lanes, one a LT and the other a RT lane.
23
2. Simplified at-grade railroad configuration: The current crossing has four tracks: dual mainline tracks, and spur and siding tracks. The spur and siding tracks were eliminated. The dual mainline track was modeled as a single track and the length of a single "long" train was used to simulate the simultaneous crossing of two trains in opposite directions. 3. Eliminated the second close-coupled intersection: The proximity of the second intersection, Butler/Enterprise, caused a "pumping" action that directed traffic at the study intersection in a patterned, but unpredictable way. Additionally, NB Enterprise traffic that might otherwise queue behind the crossing while a train was passing would be interfered with by the needs to keep the Butler/Enterprise intersection clear. However, this varied unpredictably, depending on driver behavior. Therefore, the study intersection was modeled without the Butler/Enterprise intersection. Furthermore, Enterprise was modeled with sufficient length that all queuing traffic was accommodated. While these modifications did not completely convert the study intersection into the typical commuter at-grade crossing envisioned in the research question, it was a useful compromise. This allowed the real traffic that had been captured at the site and used to calibrate and validate the model to be applied to the modified tee geometrics. This was an important benefit and the alternative was to model both an artificial intersection and artificial traffic. Whereas the artificial intersection would have been much closer to the commuter at-grade crossing envisioned by the research question, the use of artificial traffic would make it difficult to generalize the results to potential field test sites. 3.3. VEHICLE TRAFFIC USED IN THE MODEL Collecting vehicle traffic at the study site and extracting that needed for modeling was not a trivial task. Three groups were used to collect data on the traffic moving through the two intersections: one to record the traffic counts, one to simultaneously videotape intersection movements, and AZTrans supervisory staff. Data was collected for three days from Wednesday, April 23, 2003, through Friday, April 25, 2003. 3.3.1. Data Collection Procedure AZTrans, in conjunction with Traffic Data Systems (TDS), collected vehicle volume data at the intersections of Route 66 and Enterprise Road, and of Butler Avenue/Enterprise Road and Huntington Drive (see Figure 5). TDS used forty pneumatic hoses to collect 24-hour traffic volume data for three days, beginning 12:00 a.m., Wednesday, April 23, 2003, and ending 11:55 p.m., Friday, April 25, 2003. These tubes consisted of either stubs (tubes extending only to "drip line" of vehicle) or full lane tubes (tubes extending the full length of the lanes being counted). Stubs were used to record the right turn movement on WB Butler and full lane tubes were used in all other lanes. In order to collect data on internal lanes (for example, the innermost lane in a dual left-turn lane within a five-lane section), TDS "jammed" the part of the tube that extended over the outermost lanes, thus collecting data for only the innermost lane.
24
Figure 5: Vehicle Traffic Data Collection Using Pneumatic Hoses Looking east at the approaching WB Route 66 traffic at the study intersection of Route 66 and Enterprise Road. Two pneumatic hoses are in place across three lanes of traffic between the two white arrows. One hose spans the two WB TH lanes. The second hose spans all three lanes but is "jammed" for the portion that crosses the two WB TH lanes so it is only recording traffic on the WB LT lane. The recorder box is located behind a small pine tree to the left of the left arrow. Forty pneumatic hoses were used at the study intersection and the nearby intersection of Enterprise Road at Butler Ave. to capture all of the needed traffic flow data over a three-day period.
Additional double pneumatic hoses were placed at three locations: NB Enterprise (north of the Butler-Enterprise intersection and south of the Huntington cutoff), SB Enterprise (south of the Route 66-Enterprise intersection and north of the Butler-Enterprise intersection), and EB Butler (east of the Butler-Enterprise intersection), which collected data on vehicular volume, class, and speed. This field data was used as the benchmark for calibration and validation purposes in the VISSIM model. TDS checked the recording boxes daily to insure proper operation. One box, recording WB Butler at the Enterprise/Butler intersection, failed on Wednesday morning so the missing data was recollected at this location the following week during the same day and time. Five camcorders recorded queue lengths from the following three locations: Route 66/Enteprise intersection (Station 1), McDonald's Restaurant rooftop (Station 2), and 25
south of the Butler/Enterprise intersection (Station 3). These locations are shown on a map in Figure 6. Station 1, the Route 66 and Enterprise intersection, recorded vehicle queues on EB and WB Route 66. Two wide-angle lens cameras were used to record this vehicle footage at this site. Station 2, from the rooftop of the McDonald's fast food restaurant, captured footage of vehicle queues on EB Butler. Station 3, which was just south of the Butler/Enterprise intersection, recorded queue data on WB Butler, SB Enterprise and SB Huntington. Camcorder locations at both intersections used "scissor lifts" to elevate the camera platforms above the intersections, 10 feet at Station 1 and 25 feet at Station 3. Traffic footage was collected for 9 hours on Wednesday and Friday and 12 hours on Thursday. The 9 hours recorded are 6:30 a.m. to 9:30 a.m., 11:30 a.m. to 2:30 p.m., and 4:00 p.m. to 7:00 p.m. Mini-DV tapes were used and switched out every 60 minutes, except for Wednesday, when one camcorder utilized 40-minute tapes. Five NAU student research assistants from AZTrans and four cameramen from Echo Productions and Bold Eagle were hired to man the cameras in shifts, with supervisory staff from AZTrans available onsite for direction (see Figure 7). 3.3.2. Adjustments made to data provided by TDS Data from the field was organized into a Microsoft EXCEL spreadsheet and aggregated into five-minute totals by TDS and provided to AZTrans. These five-minute aggregations listed vehicle counts for nineteen stations plus eleven additional stations with vehicle counts, speeds, and tire configuration for three days of data collection. Using this dataset, AZTrans developed heavy vehicle adjustment factors for each fiveminute period. After applying the heavy vehicle factor to the data, each five-minute period vehicle count was converted to a flow rate (veh/hr). This vehicle flow rate data was entered into the VISSIM model for nineteen movements and five entry points into the network.
26
Station 1
Station 2
Station 3
Figure 6: Video Cameras Location Map Map shows locations of the three video camera stations used to record traffic flow data over the same three-day period that pneumatic hose data was collected. Stations 1 and 3 are located on "scissor lift" platforms, and each uses two cameras. Station 2 uses a single camera located on the roof of a McDonald's restaurant. 27
Figure 7: "Scissor Lifts" Aided In Obtaining Adequate Video Top photo is taken from on top of the McDonalds restaurant, at video camera Station 2, looking west across the Butler Ave--Enterprise Street intersection. The red arrow shows the location of video camera Station 3, which is also shown in the lower right photo. The lower left photo is looking south from the Route 66--Enterprise Road intersection, showing video camera Station 1 in the foreground.
3.3.3. Data Used in the VISSIM Model for Calibration and Validation AZTrans developed the VISSIM model using the existing geometry with improvements and the volumes obtained from the traffic data collection program. Appropriate time periods were extracted from the data that best represented the desired conditions at the study site. The primary conditions desired were peak vehicle traffic flow coupled with railroad crossing preemption(s) during the same time period. The initial model was developed for the time period from 8:10 a.m. to 9:20 a.m. on Friday, April 25, 2003, for calibration purposes.
28
In the developing of the VISSIM model, significant data was required beyond vehicular vehicle flows. These included vehicle speed distribution(s), vehicle type(s), routing decisions, and priority rules. Routing decisions are those routes placed in the traffic network that "lead" individual vehicles to their destination, typically through an intersection. Priority rules are used to establish right-of-way for conflicting movements. They are generally used for turning movements, stop signs, and places where vehicles merge. Vehicle speed distributions were set per observed field data, ranging from 25 mph to 40 mph, with the 85th percentile traveling at a set desired speed. Vehicle classes used in the VISSIM modeling program were identified in European terms. VISSIM is international modeling software originally developed in Germany and several of the terms used in the software reflect European terminology rather than American terminology, however, the functionality is the same (Planung Transport Verkehr AG, 2003). Passenger car types were Car 1 through Car 6 with approximate lengths of 14 feet; Sport Utility Vehicles/Trucks had lengths between 16 and 19 feet; and HGV (Heavy Goods Vehicle) had lengths between 28 and 60 feet. Cars were specified separately from Sport Utility Vehicles/Trucks so that different lengths and color identification could be entered with ease. HGV vehicle types include all heavy vehicles, including buses, that traverse the traffic network. Pedestrian and bicycle movements were omitted from the model because their volumes were insignificant. Other entered data included speed reduction zones, which were used to replicate speed conditions present in the field. Speed reduction zones were placed in all turning movements at the two intersections where short sections of low speed are typical, such as turning lanes and curves. According to the VISSIM 3.70 User's Manual, "When approaching a reduced speed area, a vehicle reduces its speed in order to reach its new (slower) speed at the beginning of the reduced speed area. The deceleration process is initiated according to the deceleration value defined. The acceleration at the end of the reduced speed area is determined by the characteristics of the driver-vehicle-unit as well as the original desired speed" (Planung Transport Verkehr AG, 2003, pp. 4-35). Turning movement speeds ranged between 5 and 26 miles per hour, depending on the type of vehicle making the turn. The Arizona Department of Transportation and the City of Flagstaff provided timing information for the signals in the traffic network. ADOT operates and maintains the signal at the intersection of Route 66 and Enterprise Road while the signal at Butler Avenue/Enterprise Road/Huntington Drive is owned and operated by the City of Flagstaff. This timing information, including normal train preemption, was entered into the VISSIM model. The intersection of Route 66 and Enterprise Road operates as an actuated uncoordinated intersection. Only one overlap is incorporated at this intersection and operates with both Route 66 WB LT and Enterprise NB LT. The Enterprise NB RT (Movement 8) never runs as a stand-alone phase and operates solely as an overlap. The movements and their phase numbering scheme are shown in Figure 8. Also the in-road detector information was entered for both intersections. Detector information was obtained both from field observations and information provided by the City of Flagstaff.
29
Route 66 (E-W)
WB TH (6) WB LT (1)
EB TH (2) EB RT (na)
N
NB LT (3) NB RT (8)
Enterprise (N-S)
Figure 8: Study Intersection With Vehicle Movement Controller Numbers The intersection movements are labeled as to direction including their controller movement (phase) number. For example, Northbound Right Turn is movement number 8. EB RT is labeled "na" because while it has an exclusive lane, it doesn't have a dedicated control phase so it moves concurrently with EB TH (2). 3.3.4. Modified Data Used in the VISSIM Model for Study Cases As discussed earlier, the two intersections as they exist today were unsatisfactory for study purposes and were modified for the modeling. The modified Tee intersection geometrics used for the study also required modifications to the vehicle data. The vehicular volume data used in the modified Tee intersection VISSIM model reflects the time from 3:00 p.m. to 6:00 p.m. at the study site. This time represents observed peak hours occurring during the three-day period of data collection. The volumes used in the modified Tee model were obtained by averaging the vehicular volume data collected from Wednesday through Friday, 3:00 p.m. to 6:00 p.m., so as to obtain a representative peak period. A peak hour factor adjustment of 0.984417 was developed from the classification data and was applied to the raw data to obtain the final volumes used in the model. 3.4. RAILROAD TRAIN CHARACTERISTICS USED IN THE MODEL The congestion experienced by the passing of a train is a function of four primary variables: The volume of vehicle traffic crossing the railroad. The volume of vehicle traffic using the nearby signalized intersection.
30
The duration of railroad crossing gates-down. The headway5 between trains. Data was collected by BNSF for a week of all train activity at the study site. The longest duration of a gates-down condition for modeling the site was established at 4.5 minutes (270 seconds), which represents 95% cumulative probability, i.e., the probability that 95% of all gates-down durations will be of this length or less. Similar values were established for the shortest and average gates-down durations of 1.5 minutes (5% cumulative probability) and 2.6 minutes (50% cumulative probability) respectively. In this report, the term "longest" train actually means the longest gates-down duration caused by a train. Similar meanings apply for the "shortest" train and "average" train. At the double-track study crossing, the "longest train" is actually two trains that cross in opposite directions. The first to cross has not cleared the crossing before the second train starts to cross. Therefore, the gates stay down continuously until both trains have cleared the crossing. While the headway between trains also effects congestion, it is a more difficult variable to quantify. While this data was collected and analyzed at the study site, its use presents difficulties when coupling with a gates-down duration. For example, it would be a rare event if the longest train was followed by the shortest headway of the next train6. While these compound probabilities could possibly have been established by collecting more data, it was decided that this would only add complexity to the modeling that wasn't useful. Studying the impacts of a single train passing at peak hour conditions was selected as the condition of most interest, and this study is limited to that focus. Detailed statistics and cumulative distribution functions of the railroad headway and gates-down durations are provided in APPENDIX B.
5
Headway is the time between successive vehicles (trains), typically measured from the front of the leading vehicle to the front of the following vehicle in seconds. What impacts vehicle congestion is the duration of the "gates-down" in combination with the interval until the next "gates-down." Since the study site is a dual mainline track, an initial "gatesdown" duration is caused by a train traveling in one direction. The subsequent "gates-down" duration is caused by a train traveling in either the opposite direction or the same direction. If the train is traveling in the opposite direction on the parallel track, it could arrive at any time during or after the previous train is at the crossing. If it is traveling in the same direction, on the same track, it is limited by the railway company's control system that governs the flow of train traffic in the same direction on the same track. This is a complex system but conceptually it sets an approximate minimum following headway between trains, which can vary depending on the railroad geometry and crossing control system at the crossing.
6
31
(blank)
32
4.
MODEL DEVELOPMENT
4.1. SELECTION OF THE MODELING ENVIRONMENT The overarching reason to use a model to test the research question is the liabilities associated with direct field-testing. If field-testing were to be performed as the first step of a research investigating changes in intersection traffic control, it would have to be on a trial-and-error basis. Obviously, safety and congestion issues preclude such an approach. For these reasons, researchers use models to test proposed changes, especially new ones, before any field-testing is even contemplated. Models can be classified in many ways (TRB HCM, 2000, pp. 31-1 to 31-6). One is to vary three dimensions: (a) scale of detail, (b) basis of analysis, and (c) method of analysis. Scale of detail is categorized into (1) large scale, that requires highly aggregated data, (2) small scale, that requires extensive disaggregate data, and (3) middle scale, which is somewhere in between as to the amount of data required. These model scales are called respectively macroscopic, microscopic, and mesoscopic. The basis of analysis can be categorized as (1) theoretical or (2) empirical. And the method of analysis can be categorized as (1) deterministic or (2) stochastic. It is important to realize that ways of classifying models are not typically an "either-or" situation as much as somewhere along a multi-dimensional continuum (Akcelik & Associates, 2005). For the purposes of exploring the research question, the parameters to be varied and tested require a high degree of detail at a microscopic level. The modeling environment has to be able to extract measures of effectiveness. Due to the variability of both the vehicle and train traffic, a stochastic modeling approach would serve best, in the form of simulation. Most traffic models have elements of both traffic flow/driver behavior theory and reliance on empirical analysis of measured traffic site data for some modeled characteristics. A microscopic traffic simulation modeling environment was chosen for use in this study. "With advances in computing technology and the ever-increasing power of personal computers, many sophisticated stochastic microscopic simulation models have been developed in the area of transportation engineering. Improved user interfaces have significantly reduced the effort needed to code and interpret the results of these simulations models. As a result, more traffic engineers are relying on microscopic simulation models to analyze complex transportation problems when analytical methods cannot provide satisfactory solutions." (Tian, et al, 2002, p. 23) A handful of microscopic traffic simulation modeling environments are available for use and have been carefully examined by the research community. Of these, VISSIM was chosen for four primary reasons: (1) high control over the vehicle-level parameters, (2) ability to use a powerful macro language to program the EWS features, (3) proven ability to use hardware-in-the loop, and (4) an update resolution of several times per second. 4.2. VISSIM MODEL CALIBRATION "Calibration is necessary because no single model can be expected to be equally accurate for all possible traffic conditions. Even the most detailed microsimulation model still 33
contains only a portion of all of the variables that affect real-world traffic conditions. Since no single model can include the whole universe of variables, every model must be adapted to local conditions. ... The objective of calibration is to improve the ability of the model to accurately reproduce local traffic conditions." (Dowling, Skabardonis, and Alexiadis, 2004) The VISSIM model was calibrated using the current existing geometric configuration at the intersection and the collected data as described in Chapter 3. The collected data from the field served as the benchmark for the calibration process. In order to represent normal traffic conditions, a calibration time period was selected in which there was the greatest number of consecutive five-minute periods where there were no train crossings at the study site. The selected time period for calibration was Friday, April 25, 2003, from 8:10 a.m. to 9:20 a.m. Once the hourly volumes were entered for their respective movements, three calibrationspecific data collection points, as shown in Figure 9, were placed in the traffic network in VISSIM. These points collected output data from the model on mean speed of all vehicles and the number of vehicles. They were placed as close as possible to the locations where the actual pneumatic hoses were located in the field during data collection. VISSIM data collection points consist of a bar that is placed in the crosssection of a link, or roadway. As simulated vehicles cross the data collection bars, designated output information is collected about individual vehicles. It is this output data that is compared to the field data in the calibration/validation process. 4.2.1. Establishment of Calibration Parameters "The analyst should attempt to keep the set of adjustable parameters as small as possible to minimize the effort required to calibrate them. Whenever practical, the analyst should use observed field data to reflect local conditions. This observed data will serve as the nonadjustable values for certain calibration parameters, thus leaving the set of adjustable parameters to a minimum." (Dowling, Skabardonis, and Alexiadis, 2004) Two calibration parameters were selected for manipulation within the VISSIM model. These two calibration parameters are speed at turning movement locations and the two parts, additive and multiplicative, of desired safety distance (car following rule). These calibration parameters were systematically set at different values with each simulation run until the model duplicated the field conditions, within acceptable difference limits. In order for simulated vehicles to replicate field speeds at locations where speeds are known (in this case, where the double pneumatic hoses were placed), not only were the speeds on the roadways set, but reduced speed areas were incorporated. Reduced speed areas slow down vehicles through its area of application and allow a return to desired speed after the area is traversed. Nineteen reduced speed zones were placed in the traffic network surrounding the study site. Seven were placed at all turning movements (WBLT, WBRT, EBLT, EBRT, NBLT, and NBRT) at the Route 66/Enterprise Road intersection. Eleven were placed at all turning movements (EBLT, EBRT, WBLT, WBRT, NBLT, NBRT, SBLT, and SBRT) at the Butler Avenue/Enterprise RoadHuntington Drive intersection. One was placed on the Huntington Drive slip lane turning movement.
34
Figure 9: VISSIM Model Showing Data Collection Points A screenshot from the VISSIM model is shown, with the data collection points used to collect output activity information from the model. Data collection points labeled A, B, and C were used in collecting the field vehicle traffic data. These same locations were used to collect model output activity regarding mean speed and the number of vehicles for use in the calibration of the model. Figure 10, Figure 11, and Figure 12 on the following pages depict the locations of these reduced speed areas. Without reduced speed areas, the vehicles traverse the intersection at the free flow speed (which ranged from 35-45 miles per hour in this model) and the resulting data in VISSIM reflect unrealistic high speeds through the traffic network. By reducing the speed in which a vehicle can traverse the turning movements, the speeds on all roads reflected more closely the field speed data. The two parts, additive and multiplicative, of desired safety distance settings (car following rule), control the saturation flow rate of the model. As described in VISSIM software manual, these are model parameters under the Weidemann (1974) psychophysical driving behavior model, which the VISSIM model uses in its implementation (PTV Planung Transport Verkehr AG, 2003). The saturation flow rate defines the number of vehicles that can free flow through a VISSIM model during one hour. 35
Figure 10: VISSIM Model Screen Display At Route 66 and Enterprise Showing Reduced Speed Areas, Links, And Connectors A screenshot from the VISSIM model is shown, with the seven reduced speed areas outlined in green. These reduced speed areas are at the intersection of Route 66 and Enterprise Road. The blue lines depict "links" in the model, which serve as roadways (or sidewalk for pedestrians) containing a designated number of lanes. The purple lines are "connectors," which serve to connect links to one another and are used to model turning movements and changes in the number of lanes (lane additions or drops).
36
Figure 11: VISSIM Model Screen Display At Enterprise and Butler Showing Reduced Speed Areas, Links, And Connectors A screenshot from the VISSIM model is shown, indicating the 11 reduced speed areas at the intersection of Butler Avenue/Enterprise Road/Huntington Drive.
37
Figure 12: VISSIM Model Screen Display Showing Huntington Slip Lane Showing Reduced Speed Area, Links, And Connectors A screenshot from the VISSIM model is shown, with the reduced speed area on the slip lane of Huntington Drive, south of the Route 66/Enterprise Road intersection.
38
4.2.2. The Calibration Process After all field information, including geometrics and vehicular volume, was entered into the model, five seeds were run in VISSIM and the results (mean speed and number of vehicles) from each seed output were averaged. These averages for simulated vehicles were compared with the values for speed and number of vehicles obtained from field data. The target calibration objective of 10% or less was set for this difference. Ideally, this target objective could be met at the resolution of 5-minute aggregations; however, this level of data is rarely available and there is little experience in calibrating a model at this resolution. After several unsuccessful attempts, the resolution was changed to 15-minute aggregations. The variability of 5-minute aggregations was large, confounding the attempts to calibrate the model using them. Twenty-nine iterations were conducted until the target calibration objective was achieved. This calibration was achieved using the 15-minute aggregations. Once the calibration objective was achieved with five seed values, twenty seed values were simulated in VISSIM, which also met the calibration objective. 4.3. VISSIM MODEL VERIFICATION After the model is calibrated, its ability to generalize for different situations should be validated using a different data set. A second data set for validation was extracted from the field data for this purpose. The validation procedure used twenty seed values and the same model parameters finalized in the calibration process. The validation data set was for Thursday, April 24, 2003, from 3:50 p.m. to 4:35 p.m., which was also a time period where there were no trains in the traffic network. The validation vehicular data was entered into the calibrated VISSIM model and the results from twenty seeds were collected. This initial run did not meet the target objective of differences of 10% or less. Therefore, the calibration model was adjusted in various ways until, in all cases, the 10% target calibration objective was met. After four attempts, a fully calibrated model was found that also met the validation goal. In other words, the model met the 10% target for both the calibration and validation data sets.
39
(blank)
40
5.
EARLY WARNING SYSTEM
The research question focuses on taking actions before a train arrives at an at-grade crossing that will mitigate the congestion that occurs after the train passes. The actions to be taken are within the context of the traffic signal control system at the nearby intersection. A proposed solution to address the research question was to design and test an Early Warning System. 5.1. EARLY WARNING SYSTEM DESIGN CONSIDERATIONS To be of most use, an ideal EWS would conceptually have these features: 1. Simple and inexpensive to design, build, and install. 2. Capable of being maintained by existing maintenance technicians with little or no new training required. 3. Controlled by the highway agency without need for any changes to the railroad control system. 4. Able to maintain the time-tested safety aspects of current at-grade crossing highway and railroad control schemes. Functionally an ideal EWS would have these components: 1. Detection: Early detection of a train approaching the at-grade crossing. 2. Prediction: Prediction of when the train will arrive at the crossing and how long it will take to clear the crossing. 3. Congestion Mitigation: Changes in the normal intersection traffic control scheme before the train arrives that will reduce the congestion caused by a train after it has passed the crossing. 4. Safety: Minimize the possibility of a vehicle-train collision. The EWS reported here tests a system that will achieve the ideal features using the components listed above. Each component is itself is a subsystem and a major undertaking. Some components were addressed more fully than others in this research because of problems encountered and resource restraints. 5.2. EWS DETECTION SUBSYSTEM The EWS detection subsystem conceptually will detect an approaching train at a much greater distance from the crossing than a typical railroad detection system currently does. Additionally, this information must be communicated to the EWS prediction subsystem. The EWS prediction subsystem will require information about both the speed and the length of an approaching train. 5.2.1. Radar Detection and Wireless Communication A radio frequency (RF) Doppler radar detector has been used for train detection in previous research. Those systems were pioneered by Leonard Ruback at the Texas 41
Transportation Institute (Ruback 2001, TTI 2005-1). Ruback built systems in his lab from various components and has tested them in the field in various locations. Such an approach could be used; however, with the increasing use of radar speed detectors for ITS and enforcement uses1, off-the-shelf devices are now more readily available and would simplify the subsystem and make it easier to maintain. The radar detector would be pole mounted but would be located outside of railroad rightof-way (TTI 2005-2). It would be able to detect a train's presence and speed and send this information to the EWS prediction subsystem. It would also be able to send when the train was no longer detected. The detector would have the ability to induce the train's speed and possibly its length as well. If the length could not be induced by the sensor, it could be calculated by the prediction subsystem from the raw data collected by the detector, i.e., speed, time presence is first detected, and time presence is last detected. Another component needed for the EWS detection subsystem is a communication system that will send the detected train information to the EWS prediction subsystem. The prediction subsystem is probably best located in the same cabinet as the regular intersection traffic control system. Wireless sending and receiving devices will serve this purpose, when designed for outdoors field use such as in traffic applications. Spread spectrum technologies are one method typically employed. Several vendors offer products in this category using either direct sequence or frequency hopping techniques to produce the spread spectrum output. Spread spectrum equipment operating in the popular unlicensed 900 MHz ISM (Industrial, Scientific, and Medical) band would serve the purpose. These require a transmitter located on the pole with the detector and a receiver located in the intersection traffic control cabinet. Often line-of-sight must be maintained, which may require the use of repeater stations, as would long distances. However, these devices draw low power and can be solar powered. More than one pole-mounted sensor may be required. For example, a second sensor may be useful closer to the crossing. The data received from this second sensor could be used by the prediction subsystem to recalculate train arrival time and duration. If this has changed sufficiently, the actions taken by the congestion mitigation subsystem could be retimed or aborted. 5.2.2. Time Domain Reflectometry (TDR) Detection An experimental detection device has been developed under the IDEA2 program (TRB IDEA). The original intent of this system was to detect breaks in the railroad tracks. For this purpose, the device was mounted in the cab of the train driver. The device induces an electrical pulse into the rails ahead of the first locomotive axle. This pulse travels
1
Doppler radar devices are used in photo radar speed and red-light running systems, traffic monitoring systems for use by Traffic Control Centers, and variable message signs that display an approaching motorist of his vehicle speed. The Innovations Deserving Exploratory Analysis (IDEA) program provides start-up funding for promising, but unproven, innovations in surface transportation systems. The program is managed by the Transportation Research Board and supported by the Federal Railroad Administration, the Federal Transit Administration, and the Federal Motor Carrier Safety Administration.
2
42
forward through the rails until any significant electrical variation is encountered in the track, whereupon a portion of the pulse is reflected back to be received and analyzed at the train. The phase of the returning pulse will indicate if the hazard is a broken rail or track occupation, and the exact amount of time delay will give the distance ahead. If another train is ahead on the same track, the device can constantly calculate the distance and relative approach speed of the second train. In discussions with the developer of this device, Steven Turner of Analogic Engineering3, he indicated that this detection device might be used for the EWS detection subsystem. For this use, the detection device would be used at a fixed location at the crossing. The TDR detector would constantly sense for an approaching train. When one is detected, the detector would constantly calculate the speed and distance to the approaching train. It could continuously transmit this information and would therefore detect any change in speed that the EWS prediction subsystem could use to change or abort its earlier predictions. Since the TDR detector would be located at the crossing, communication to the nearby intersection traffic controller cabinet could be hardwired or wireless. However, if the length of the train is also needed, a second TDR detector would have to be installed some distance from the crossing. This second detector would detect the "back" of the train and transmit its data to the first TDR detector, located at the crossing, which would detect the "front" of the train. Since both detectors would be simultaneously giving the distance to the front and back of the train and the distance between the detectors is known, the length of the train can be calculated. This TDR system, configured for use in a train driver's cab, is currently undergoing testing at the Transportation Technology Center, Inc. (TTCI) in Pueblo, CO. TTCI focuses on railroad and transit research and operates a laboratory that includes 48 miles of railroad track to test a wide variety of rail components, including rolling stock, track components, signal, and safety devices. The TDR detection device has not been configured or scheduled for testing for use in the EWS detection subsystem and therefore its usefulness for this application remains unknown. Additionally, since it would be connected directly to the railroad's tracks, the system would not be controlled by the highway agency but would have to be controlled by the railroad company. But while the TDR detection device needs additional testing before it could be used, it does offer the significant potential benefit of providing continuous speed and distance data whereas a radar detector can only give "spot" speed/length information of the train where the detector is physically located. 5.3. EWS PREDICTION SUBSYSTEM An EWS prediction subsystem would be a small field-grade microprocessor located in the intersection traffic control cabinet. The data from the EWS detection subsystem would be received by the detection subsystem's data receiver located in the cabinet and ported to the microprocessor. The microprocessor would contain a clock that would
3
Steven Turner, Analogic Engineering, Inc., Guernsey, WY.
43
time-stamp incoming data. From this data it could predict the time the train would arrive at the crossing and the time interval before it cleared the crossing from a simple or sophisticated prediction algorithm. A simple approach, and one that has proved successful at other sites (Ruback 2001), is a simple speed versus distance to calculate time of arrival. Depending on the railroad speed limit changes between the detector and the crossing, this method could be within the accuracy needed. Railroad companies strictly enforce their speed limits and trains change speeds slowly. If a specific site has a complex set of parameters that might affect the speed of a train between the detector and the crossing, a more sophisticated algorithm could be developed to help account for this complexity. Conceptually, this is possible because a significant number of the parameters between the detector and the crossing are fixed, e.g., distances, speed limit change points, spurs, sidings, etc. These fixed parameters make it easier to accurately predict some of the changing variables. For example, if a train occasionally stops before it reaches the crossing, the behavior of a train that does so might have a recognizable pattern of speed changes at specific locations, etc. These speed changes might be detectable by positioning of multiple radar-type detectors at specific points or by using a continuous-type detector. When such a pattern was detected, the arrival prediction could be modified or aborted. 5.4. EWS CONGESTION MITIGATION SUBSYSTEM The microprocessor used for the EWS prediction subsystem would also contain the EWS congestion mitigation subsystem. Therefore, the predictions needed by the congestion mitigation subsystem would be available to it when needed. The congestion mitigation subsystem uses the EWS algorithm developed for the specific site. This system conceptually wraps around the EWS safety subsystem. Its purpose is to take actions when a train approaches before the normal train preemption occurs. These actions interrupt the normal traffic signal cycle and allocate the green time differently. If successful, this reallocation of green time before the train arrives will reduce the congestion that typically occurs after the train has passed. 5.4.1. Principle of Costs and Benefits At the research site, when a train is passing the crossing, the movements and phase numbers that are restricted from moving are WB LT (1), NB RT (8), NB LT (3), and EB RT (na), as shown by Figure 8. Therefore, it is these movements that are the focus of actions taken before the train arrives. Conceptually, this means that "extra" green time is given to these movements before the train arrives and the crossing gates come down. An important concept that governs giving "extra" green time to any movement is that it must be "stolen" from another movement. For example, in order to interrupt the normal cycle allocations of green and give WB LT (1) some "extra" green, it must be taken (stolen) from other movements in the normal cycle that was interrupted. If in this example, EB TH (2) was green and it was interrupted (cut short) to give WB LT (1), then the "extra" green given to WB LT (1) was "stolen" from EB TH (2). As a result, more vehicles would be delayed on EB TH (2) when green is "stolen" from it than if the normal cycle would not have been interrupted. This is the cost associated with 44
giving some "extra" green time to EB LT (1). The benefit is that "extra" green time will reduce the delay for those vehicles that receive it. 5.4.2. Measurement of Costs Versus Benefits In order for costs to be compared to benefits, a common measurement of both must be taken. These are called Measures of Effectiveness, or, they could be called Performance Measures (PMs). The MOE used must look at the intersection as a whole rather than as individual movements. Three MOEs were selected by the project's Technical Advisory Committee to be measured and analyzed for the study site. 1. Average Delay measured in seconds per vehicle, using all vehicles to pass through the intersection during a set period of time. 2. Average Travel Time measured in seconds per vehicle, using all vehicles to pass through the intersection during a set period of time. 3. Average Queue length measured in feet, using all vehicles to pass through the intersection during a set period of time. Two other MOEs were discussed by the TAC and would have been useful except that the VISSIM modeling environment used for the study would not capture them adequately. These were the Number of Cycles to Clear and Stopped Time. 5.4.3. Method to Capture Costs Versus Benefits -- Before and After Study In order to compare the costs versus the benefits of the EWS congestion mitigation subsystem, a method must be established to do this. This method is typically called a "Before and After" study. This title, while used in this report, is slightly misleading. Technically the method is a "With and Without" study. The Before (Without) analysis models the intersection without using the EWS. The After (With) analysis models the intersection using the EWS. An important principle is to duplicate exactly the entire modeling environment for both the Before and After analyses, only varying the specific EWS activities in the After analysis. This cannot be done in a field situation because many things change between the Before and After analyses besides the EWS activities. For example, the vehicle traffic changes since this is a stochastic process and is never duplicated exactly from one time to the next. Similarly, train traffic changes, as does a whole host of other factors. The only way to duplicate the entire environment exactly is to use a model that can duplicate all conditions exactly while changing only those needed for the After analysis. Microscopic simulation traffic models are the tools used for this purpose. One such modeling environment, VISSIM, was used for this study. It allows the capture of the MOEs of both the Before and After analyses and compare them. It is this comparison that yields the costs and benefits. 5.4.4. Stochastic Models Require Multiple Runs Microscopic traffic simulation models attempt to model the types of variability that actually occur at a site. For example, traffic varies from day to day and hour to hour. A typical peak hour traffic stream on Tuesday of one week, while similar to the traffic on the Tuesday of the following week, is not exactly the same. In fact, variability can be 45
significant. The model tries to capture this variability so that each time the model is run, it will vary the traffic flow in a definable, but stochastic way. Any run can be repeated exactly because it depends on an initial starting number, called the "seed." So if the same seed is used on a second run, it will produce the exact same results and MOEs as the first run. But if a different seed is used, the same model will vary the traffic flow and give different results. The strength of a microscopic simulation model is this variability. It provides a different, but probable, MOE output for each run. This models actual traffic in the field. So a scenario can be tested under different, but probable conditions, using a series of runs. The MOE from each run, however, is only a snapshot of what is happening. To get a true picture of what is happening, all the runs must be considered together. This can be done in several ways. The most useful is to average the MOEs from a series of runs and use this average MOE for analysis. However, in some cases the maximum and/or minimum value from a series of runs might be useful, for example in evaluating queue length. An accepted minimum number of runs varies from 5 to 10. The primary work done in this study uses 10 runs, but some of the secondary issues were explored with only 5 runs, which conserved resources. 5.4.5. Principle of Availability of Vehicles to Receive Benefit A subtle but critical principle when dealing with mitigating actions is that something done now will affect something that is forecast to happen in the future. In developing an EWS, the premise is that something is done before a train arrives at a crossing that will relieve congestion that will build up and be present once the train has cleared the crossing. Simply stated, the EWS attempts to move vehicles through the railroad crossing before the train arrives--vehicles that would normally have to wait until the train passed. The subtle, but necessary, condition for this to happen is that the vehicles that have to wait for the train to pass must arrive at the intersection early enough to be able to use the "extra" green they receive. In other words, unless a heavy volume of vehicles, which would be held up by the train, are available to move through the crossing when the EWS is initiated, then the "extra" green given to this movement is not used by a significant number of vehicles. The "extra" green time is not fully used because not enough vehicles are present to use it. This means that vehicles that arrive from right after the EWS has ended, until the train has passed, mainly cause the congestion. 5.5. EWS SAFETY SUBSYSTEM Safety is the primary objective of the special preemption control scheme currently used at an intersection when a train is passing at a nearby at-grade crossing. This scheme clears the tracks before the train arrives and withholds movement toward the crossing while the train is passing. It is triggered by a preemption signal sent by the railroad to the traffic signal controller. The traffic signal controller allows other preemptions, like the EWS, but requires each to have a priority assigned to it. The railroad preemption has a priority of one and overrides all other preemption signals as well as all other normal functions of the controller to 46
address the approaching train. The EWS maintains this safety by not interfering with either the preemption signal from the train or the signal controller's response to it. If the EWS is already activated when a railroad preemption signal is received, the EWS will be immediately terminated so the preemption control scheme can begin. Likewise if the preemption control scheme is running and the EWS sends a signal to begin, the EWS signal will be ignored until the train has cleared the crossing that the railroad preemption control scheme has finished. These actions are already a part of a standard controller logic and are not changed in any way by the EWS. Therefore, a key component of the safety subsystem of the EWS is to never interfere with the activation of the train preemption. By keeping this in place, the crossing safety experienced before an EWS is in

Click tabs to swap between content that is broken into logical sections.

Copyright to this resource is held by the creating agency and is provided here for educational purposes only. It may not be downloaded, reproduced or distributed in any format without written permission of the creating agency. Any attempt to circumvent the access controls placed on this file is a violation of United States and international copyright laws, and is subject to criminal prosecution.

Congestion Mitigation at Railroad-Highway At-Grade Crossings
Final Report 557
Prepared by: Craig A. Roberts, Ph.D., P.E., Principal Investigator Jamie Brown-Esplain, Research Engineer AZTrans: The Arizona Laboratory for Applied Transportation Research Northern Arizona University Department of Civil and Environmental Engineering Flagstaff, AZ 86004-5600
October 2005
Prepared for: Arizona Department of Transportation 206 South 17th Avenue Phoenix, Arizona 85007 In cooperation with U.S. Department of Transportation Federal Highway Administration
The contents of this report reflect the views of the authors who are responsible for the facts and accuracy of the data presented herein. The contents do not necessarily reflect official views or policies of the Arizona Department of Transportation or the Federal Highway Administration. The report does not constitute a standard, specification, or regulation. Trade or manufacturers' names that appear herein are cited only because they are considered essential to the objectives of the report. The U.S. Government and the State of Arizona do not endorse products or manufacturers.
This ATRC report is available on the Arizona Department of Transportation's Internet site.
Technical Report Documentation Page
1. Report No.
FHWA-AZ-05-557
4. Title and Subtitle
2. Government Accession No.
3. Recipient's Catalog No. 5. Report Date
Congestion Mitigation at Railroad-Highway At-Grade Crossings
October 2005
6. Performing Organization Code
7. Author
8. Performing Organization Report No.
Craig A. Roberts, Ph.D., P.E., Principal Investigator Jamie Brown-Esplain, Research Engineer
9. Performing Organization Name and Address 10. Work Unit No.
AZTrans: The Arizona Laboratory for Applied Transportation Research Northern Arizona University Civil and Environmental Engineering Department P.O. Box 15600 Flagstaff, AZ 86011-5600
12. Sponsoring Agency Name and Address
11. Contract or Grant No. SPR-PL-1(63)557 JPA 02-209 / R0557 15P
13. Type of Report & Period Covered
ARIZONA DEPARTMENT OF TRANSPORTATION 206 S. 17th Avenue, Phoenix, Arizona 85007 ADOT Project Manager: Stephen R. Owen, P.E. *with additional funding support from the City of Flagstaff and Northern Arizona University
15. Supplementary Notes
FINAL REPORT March 2003 - November 2005
14. Sponsoring Agency Code
Prepared in cooperation with the U.S. Department of Transportation, Federal Highway Administration
16. Abstract ?
Rapid population growth in Arizona has created several large residential areas that rely on the State highways to provide their primary, daily commuting route. When these commuter routes cross an at-grade railroad crossing, a train passing during peak traffic hours often causes severe congestion. State resources are inadequate to provide flyovers for all of these train crossings and their numbers are forecast to increase. The safety and congestion problems arising from these commuter at-grade crossings are the focus of this research. A study site was selected, train and traffic data were collected, a microscopic traffic simulation model was prepared, and an Early Warning System (EWS) algorithm was developed. The EWS algorithm gives "extra" green time to (train) conflicting traffic movements before the train arrives, taking the time from the other movements. Five cases were studied, each having two to six scenarios. Four major variables were studied: (1) crossing gates down time, (2) length of time the MOEs were collected, (3) conflicting movements traffic volumes, and (4) predicted arrival time error. The EWS algorithm was also successfully programmed into a NEMA controller using Hardware-in-the-Loop to couple it to the simulation model. Four generalizations are tentatively supported by the results but additional site studies are required for verification. First, the complex dynamic interplay of geometrics and train and traffic volumes makes the EWS effectiveness highly site dependent. Second, there must be enough pre-train vehicles present on conflicting movements that derive delay improvement to overcome the increase in delay to the other movements. Third, for safety reasons, an increase in overall intersection delay caused by the EWS may be justified to reduce long queues from backing-up into other intersections or onto freeways. Fourth, rather than control signal timing, the EWS may be used to reduce congestion by alerting drivers with a DMS of a train's imminent arrival so they can take alternate routes. While the EWS was ineffective for the study site, the results may have been confounded by insufficient pre-train queue sizes and lack of a single dominant commuter movement (the study site had strong cross flows). A follow-up study is recommended at a site with more favorable geometry and traffic volumes.
17. Key Words 18. Distribution Statement
Microscopic Simulation Models, At-Grade Highway-Railroad Crossings, Railroad Grade Crossings, Preemption, Hardware-inthe-Loop, HIL, VISSIM, CID, DSM, ITS, Model Calibration
19. Security Classification 20. Security Classification
Document is available to the U.S. Public through the National Technical Information Service, Springfield, Virginia, 22161
21. No. of Pages 22. Price
23. Registrant's Seal
Not Applicable
Unclassified
Unclassified
104
SI* (MODERN METRIC) CONVERSION FACTORS
APPROXIMATE CONVERSIONS TO SI UNITS
Symbol in ft yd mi in2 ft2 yd2 ac mi2 fl oz gal ft3 yd3 When You Know inches feet yards miles square inches square feet square yards acres square miles fluid ounces gallons cubic feet cubic yards Multiply By To Find millimeters meters meters kilometers square millimeters square meters square meters hectares square kilometers milliliters liters cubic meters cubic meters Symbol mm m m km mm2 m2 m2 ha km2 mL L m3 m3 Symbol mm m m km mm2 m2 m2 ha km2 mL L m3 m3
APPROXIMATE CONVERSIONS FROM SI UNITS
When You Know millimeters meters meters kilometers square millimeters square meters square meters hectares square kilometers milliliters liters cubic meters cubic meters Multiply By To Find inches feet yards miles square inches square feet square yards acres square miles fluid ounces gallons cubic feet cubic yards Symbol in ft yd mi in2 ft2 yd2 ac mi2 fl oz gal ft3 yd3
LENGTH
25.4 0.305 0.914 1.61
LENGTH
0.039 3.28 1.09 0.621
AREA
645.2 0.093 0.836 0.405 2.59
AREA
0.0016 10.764 1.195 2.47 0.386
VOLUME
29.57 3.785 0.028 0.765
VOLUME
0.034 0.264 35.315 1.308
NOTE: Volumes greater than 1000L shall be shown in m3.
MASS
oz lb T ounces pounds short tons (2000lb) 28.35 0.454 0.907 grams kilograms megagrams (or "metric ton") Celsius temperature g kg mg (or "t")
?
MASS
g kg Mg grams kilograms megagrams (or "metric ton") Celsius temperature 0.035 2.205 1.102 ounces pounds short tons (2000lb) oz lb T
?
TEMPERATURE (exact)
Fahrenheit temperature foot-candles foot-Lamberts poundforce poundforce per square inch 5(F-32)/9 or (F-32)/1.8
F
C
?
TEMPERATURE (exact)
1.8C + 32 Fahrenheit temperature foot-candles foot-Lamberts
C
?
F
ILLUMINATION
fc fl lbf lbf/in2 10.76 3.426 4.45 6.89 lux candela/m2 Newtons kilopascals lx cd/m2 N kPa lx cd/m2 N kPa lux candela/m2
ILLUMINATION
0.0929 0.2919 0.225 0.145 fc fl
FORCE AND PRESSURE OR STRESS
FORCE AND PRESSURE OR STRESS
Newtons kilopascals poundforce lbf poundforce per lbf/in2 square inch
SI is the symbol for the International System of Units. Appropriate rounding should be made to comply with Section 4 of ASTM E380
TABLE OF CONTENTS
EXECUTIVE SUMMARY 1. INTRODUCTION 1.1. MOTIVATION FOR RESEARCH 1.2. SCOPE OF THIS RESEARCH 1.3. ORGANIZATION OF THE REPORT 2. PROBLEMS WITH AT-GRADE HIGHWAY-RAILROAD CROSSINGS 2.1. TRAIN SAFETY 2.2. VEHICLE SAFETY 2.3. VEHICLE CONGESTION 3. SITE SELECTION, GEOMETRICS, AND TRAFFIC 3.1. SELECTION OF THE STUDY SITE 3.1.1. Railroad Equipment and Operations Used at the Site 3.1.2. Traffic Signal Equipment and Operations Used at the Site 3.2. SITE GEOMETRICS AND MODIFICATIONS FOR MODEL 3.2.1. Current Geometrics at the Study Site 3.2.2. Modified Tee Intersection Geometrics Used for the Study 3.3. VEHICLE TRAFFIC USED IN THE MODEL 3.3.1. Data Collection Procedure 3.3.2. Adjustments Made To Data Provided By TDS 3.3.3. Data Used in the VISSIM Model For Calibration And Validation 3.3.4. Modified Data Used in the VISSIM Model for Study Cases 3.4. RAILROAD TRAIN CHARACTERISTICS USED IN THE MODEL 4. MODEL DEVELOPMENT 4.1. SELECTION OF THE MODELING ENVIRONMENT 4.2. VISSIM MODEL CALIBRATION 4.2.1. Establishment of Calibration Parameters 4.2.2. The Calibration Process 4.3. VISSIM MODEL VERIFICATION 5. EARLY WARNING SYSTEM (EWS) 5.1. EARLY WARNING SYSTEM DESIGN CONSIDERATIONS 5.2. EWS DETECTION SUBSYSTEM 5.2.1. Radar Detection and Wireless Communication 5.2.2. Time Domain Reflectometry (TDR) Detection 5.3. EWS PREDICTION SUBSYSTEM 1 7 7 9 9 11 11 12 14 15 15 15 19 22 22 23 24 24 26 28 30 30 33 33 33 34 39 39 41 41 41 41 42 43
EWS CONGESTION MITIGATION SUBSYSTEM 5.4.1. Principle of Costs and Benefits 5.4.2. Measurement of Costs versus Benefits 5.4.3. Method to Capture Costs versus Benefits -- Before and After Study 5.4.4. Stochastic Models Require Multiple Runs 5.4.5. Principle of Availability of Vehicles to Receive Benefit 5.5. EWS SAFETY SUBSYSTEM 6. EWS CONGESTION MITIGATION ALGORITHM DEVELOPMENT 6.1. ALGORITHM DEVELOPMENT 6.1.1. EWS Algorithm Logic Concepts 6.1.2. Application of the Algorithm at the Study Site 6.1.3. Limitations Imposed on the Algorithm 6.2. INDEPENDENT ALGORITHM TESTING 7. BEFORE AND AFTER RESULTS 7.1. PARAMETERS USED FOR EWS CONGESTION MITIGATION 7.2. BEFORE AND AFTER CASES STUDIED 7.3. SUMMARY OF RESULTS 7.3.1. Duration Of Gates Down At Crossing 7.3.2. Duration Of MOE Period 7.3.3. Vehicle Traffic Volume Increases On Conflicting Movements 7.3.4. Early and Late Train Arrivals Versus Predicted On-Time Arrival 7.3.5. Impacts on Targeted Queue Lengths 8. HARDWARE-IN-THE-LOOP (HIL) TESTING 8.1. BENEFITS OF HIL TESTING 8.2. METHODOLOGY AND EQUIPMENT 8.3. IMPLEMENTATION USING NEMA TRAFFIC CONTROLLER 8.4. SUMMARY OF RESULTS 9. CONCLUSIONS 9.1. EFFECTIVENESS HIGHLY DEPENDENT ON THE SITE 9.2. VEHICLES MUST BE PRESENT TO USE THE EWS GREEN TIME 9.3. QUEUE LENGTH MAY SUPPORT INCREASED EWS DELAY 9.4. EWS MAY BE USEFUL FOR OTHER PURPOSES 10. RECOMMENDATIONS
5.4.
44 44 45 45 45 46 46 49 49 49 50 51 52 53 53 53 57 57 60 62 64 66 69 69 70 71 73 75 75 76 76 76 77
APPENDIX A. LITERATURE REVIEW A.1. MICROSCOPIC TRAFFIC SIMULATION MODELS A.2. ALGORITHM DEVELOPMENT A.3. HIGHWAY-RAILROAD CROSSING SIGNAL PREEMPTION A.4. HIGHWAY-RAILROAD CROSSING ISSUES A.5. HARDWARE-IN-THE-LOOP SIMULATION APPENDIX B. RAILROAD TRAFFIC DATA COLLECTION B.1. RAILROAD DATA COLLECTION METHODOLOGY B.2. GENERAL CHARACTERISTICS OF RAILROAD TRAFFIC DATA APPENDIX C. EWS CONGESTION MITIGATION ALGORITHM PROGRAMMING C.1. VISSIM MACRO LANGUAGE C.2. SYNOPSIS OF ALGORITHM LOGIC C.2.1. Position of Train Corresponds to Three States REFERENCES
79 79 81 82 83 84 85 85 85 89 89 89 90 95
LIST OF TABLES
Table 1: Table 2: Table 3: Table 4: Project 557: Technical Advisory Committee Members Overview Of Case Attributes Overview Of Case Runs Train Crossing Summary At The Study Site 10 55 56 86
LIST OF FIGURES
Figure 1: Aerial Photos Of The Study Site ...................................................................... 16 Figure 2: Photos Of The At-Grade Crossing At The Study Site...................................... 17 Figure 3: Photo Of At-Grade Crossing Equipment At The Study Site............................ 18 Figure 4: Photo Of The Intersection At The Study Site .................................................. 22 Figure 5: Vehicle Traffic Data Collection Using Pneumatic Hoses. ............................... 25 Figure 6: Video Cameras Location Map.......................................................................... 27 Figure 7: "Scissor Lifts" Aided In Obtaining Adequate Video. ...................................... 28 Figure 8: Study Intersection with Vehicle Movement Controller Numbers.................... 30 Figure 9: VISSIM Model Showing Data Collection Points............................................. 35 Figure 10: VISSIM Model Screen Display Showing Route 66/Enterprise Showing Reduced Speed Areas, Links, And Connectors .............................................. 36 Figure 11: VISSIM Model Screen Display Showing Enterprise/Butler Showing Reduced Speed Areas, Links, And Connectors .............................................. 37 Figure 12: VISSIM Model Screen Display Showing Huntington Slip Lane Showing Reduced Speed Area, Links, And Connectors................................................ 38 Figure 13: Delay For Different Gates Down Durations Using EWS On WB LT ........... 59 Figure 14: Delay For Different Gates Down Durations Using EWS On NB .................. 59 Figure 15: Delay For Different MOE Duration Periods Using EWS On WB LT........... 61 Figure 16: Delay For Different MOE Duration Periods Using EWS On NB.................. 61 Figure 17: Delay For Increased Relative Volumes Using EWS On WB LT................... 63 Figure 18: Delay For Increased Relative Volumes Using EWS On NB ......................... 63 Figure 19: Delay For Early, Late, And On-Time Arrivals Using EWS On WB LT ....... 65 Figure 20: Delay For Early, Late, And On-Time Arrivals Using EWS On NB .............. 65 Figure 21: Impact On Targeted Queue Using EWS On WB LT .................................... 67 Figure 22: Impact On Targeted Queue Using EWS On NB........................................... 67 Figure 23: Hardware-In-The-Loop Schematic Using McCain-NIATT CID II ............... 70 Figure 24: Econolite Controller--CID II--VISSIM Model Setup .................................... 71 Figure 25: Modeled Volumes During Peak 30 Minutes Centered On Train Arrival....... 75 Figure 26: Empirical CDF Of Train Headways At The Study Site ................................. 87 Figure 27: Empirical CDF Of Gates-Down At The Study Site ....................................... 88 Figure 28: NEMA 8-Phase Controller Configuration...................................................... 90
SIGNIFICANT TERMS, ACRONYMS, AND ABBREVIATIONS
ADOT AM Peak and PM Peak Approach At-grade Crossing ATRC AZTrans Arizona Department of Transportation The peak vehicle traffic flows that typically occur in the morning due to home-to-work trips and in the evening due to work-to-home trips. All lanes of traffic moving towards an intersection from one direction. The intersection of a roadway and a railroad track(s) at the same elevation or grade. Arizona Transportation Research Center: administers the research activity of ADOT and the publication of the results. The Arizona Laboratory of Transportation, the research unit at Northern Arizona University, Department of Civil and Environmental Engineering that conducted this study. Burlington Northern Santa Fe Railway Company Cumulative Distribution Function is the function that gives the cumulative frequency or cumulative probability of a random variable. Computer Interface Device is a combination of hardware and software that allows an actual traffic signal controller to be linked to a computer and operate as part of a traffic simulation model. In this study, an at-grade crossing used by a large number of travelers making daily home-to-work and work-to-home trips. In this study, a traffic movement that has to cross the railroad track before entering or after leaving a nearby intersection. See "Nonconflicting Moment." Early Warning System ? a software or algorithm used to control an intersection's traffic signal system before a train arrives at a nearby at-grade crossing. Federal Highway Administration When a roadway is grade separated to cross a railroad, by either passing over the railroad or the railroad passing over the roadway. Federal Railroad Administration Hardware-in-the-Loop simulation refers to a computer simulation in which some of the components of the simulation have been replaced with actual hardware. The hardware is fully functioning, responding to the simulation environment as if it were a real environment. Intelligent Transportation System
BNSF CDF CID
Commuter At-grade Crossing Conflicting Movement EWS
FHWA Flyover FRA HIL
ITS
MOE Movement
Measure of Effectiveness A path through an intersection. For this study site (see Figure 8), the principal traffic movements and directionalities are defined as follows: NB: Northbound; SB: Southbound; EB: Eastbound; WB: Westbound LT: Left Turn; RT: Right Turn; TH: (Straight) Through
MUTCD NEMA Nonconflicting Movement PM Preemption Control Run
Manual of Uniform Traffic Control Devices National Electrical Manufacturers Association A traffic movement that does not have to cross the railroad track before entering or after leaving a nearby intersection. See "Conflicting Movement." Performance Measure The transfer of normal operation of a traffic control signal to a special control mode of operation. Microscopic traffic simulation software generates a result using several stochastic processes. In order to generate an approximately random number for these processes, a beginning number is used. This beginning number is called a seed and the generation of the results is called a run. See "Run." Technical Advisory Committee Project sub-consultant, Traffic Data Systems, Inc. Vehicle Actuated Programming is the name of the macro language for VISSIM. A microscopic traffic simulation modeling software originally developed in Germany and maintained in the United States by PTV America, Inc.
Seed TAC TDS VAP VISSIM
EXECUTIVE SUMMARY
Several major Arizona highways are located parallel to active railroads. Population growth in the State has been rapid over the last 40 years and is projected to continue. Most of this growth has occurred in the major cities and towns, pushing them outwards along the State highway routes. This has created many large residential areas that rely on State highways to provide the primary, and often only, daily commuting route. When these commuter routes cross an at-grade railroad crossing, a train passing during peak traffic hours often causes congestion that delays traffic and may back queues into adjacent intersections or onto freeways, causing operational and safety concerns for the Arizona Department of Transportation (ADOT). Additional contributing factors to the congestion and safety concerns are the increasing traffic on the railroad lines and the increasing number of these types of crossings, which far outstrip the State's ability to provide grade-separated railroad crossings. The safety and congestion problems arising from these commuter at-grade crossings are the focus of this research for ADOT, which investigates these central issues: Research Question: Can solutions be applied at a signalized intersection, before a train passes a nearby at-grade highway-railroad crossing, that will mitigate the congestion that will occur after the train has passed? Furthermore, can this be accomplished using a standard traffic signal controller? Operational Issues The current organizational and operating systems of the railroad company and the agency that operates adjacent traffic signals have evolved over time, and each may resist change for safety and liability reasons. At an at-grade crossing, the right-of-way corridor is owned by the railway company, which also owns and operates the gates and lights that comprise the active system that alerts drivers to an approaching train. The traffic signal system at the nearby intersection is owned and operated by the city, county, or state agency that owns the roadway. The railroad's warning control system and the traffic signal control system are not integrated, and operate independently. It is critical for the nearby intersection traffic signal system to know of an approaching train so that it can take appropriate action to reduce safety problems. This is currently done by the railroad control system sending a signal to the traffic signal control system indicating a train is approaching the crossing, and later sending another signal that the train has cleared the crossing. When this signal is received, the traffic signal system operates independently to address the situation by altering its intersection control scheme in a manner known as train preemption, or simply "preemption." During preemption, the traffic signal control system does four things: (1) it safely interrupts whatever movements are currently timing and gives the green to the movements that are queued across the railroad tracks, (2) it then switches to a sequence that gives green only to non-conflicting movements and withholds green from all conflicting movements while the train passes (a conflicting movement is one that has to cross the railroad track before entering or after leaving the nearby intersection), (3) after the train has passed, it switches to a designated movement (typically the one that is 1
waiting behind the crossing gates), and (4) lastly, it places a call on another designated movement while releasing control back to the normal cycle sequence. The train preemption control scheme's primary purpose is safety; congestion mitigation is a secondary goal that occurs only after the train has passed. When vehicle volumes over the at-grade crossing are sufficiently large, and/or when the duration and/or frequency of the passing trains is sufficiently high, the preemption control scheme may be insufficient to clear all of the vehicles. This creates congestion that may cause operational problems for the roadway system. Depending on the geometrics involved, vehicle queues may extend back considerable distances into other intersections, or along freeway ramps onto the freeway itself. In some cases, it can take several cycles for queued vehicles to clear the intersection, causing considerable delay to drivers. The congestion problem is exacerbated if a second train passes before the congestion from the first train clears. Study Site Geometrics and Traffic Study site candidates required two primary characteristics: (1) they must be a commuter at-grade crossing and (2) the nearby signalized intersection must be on a State highway. Ideally the site would have severe congestion caused by passing trains. The study site selected was ADOT's Route 66 intersection with Enterprise Road in Flagstaff, Arizona. This site was chosen when the City of Flagstaff became an active secondary sponsor for the research. In retrospect, however, this intersection proved less than ideal due to its unique geometry and traffic patterns. The study intersection is a "tee" with Route 66 running east-west, and Enterprise Road as the north-south leg that ends at the intersection (see Figure 1). The east-west railroad tracks are parallel to Route 66, and cross Enterprise Road approximately 75 feet south of the intersection. The geometrics of Enterprise were recently upgraded to two northbound left-turn lanes (NB LT) and one northbound right-turn lane (NB RT). The basic Route 66 geometrics were unchanged, consisting of two EB TH (eastbound through) lanes, one EB RT lane, two WB TH (westbound through) lanes, and one WB LT lane. Each of these movements has its own signal head except EB RT, which has its own stacking lane but no signal head. The normal signal cycle at the intersection has three phases and sequence in this order: (1) WB LT, WB TH, and NB RT; (2) EB TH and EB RT to move also; and (3) NB TH and NB RT. In the standard NEMA controller used at the site, NB RT operates as an overlap with WB LT and also as an overlap with NB LT. It is allowed to do this by giving it its own phase designation, but this phase only operates as an overlap. Right turns on red after stop are allowed for both the NB RT and the EB RT. The railroad crossing is owned and operated by the Burlington Northern Santa Fe (BNSF) Railway Company. It is an active crossing using advance warning signs, crossbucks, pavement markings, bells, gates, and flashing lights. BNSF's control system sends the signal to the intersection traffic signal control system indicating a train is approaching and another signal indicating the train has cleared the crossing. These signals allow ADOT to begin and end the special train preemption traffic control scheme.
2
An Early Warning System (EWS) was developed for this study to address the research question. After applying the EWS to the simulation model developed for the study site, it became apparent that the recent geometric improvements to the study site reduced the congestion sufficiently to mask any congestion mitigation improvement potentially attributable to the EWS. The study site simulation was therefore altered to reflect its geometry before the recent construction and restriping. This changed the study site model by (1) reducing the NB LT to only one lane, (2) increasing the length of the EB RT stacking lane by about 25 feet, and (3) reducing the Enterprise Road SB (southbound) lanes leaving the intersection from two to one. The railroad-crossing model was also simplified to two mainline tracks, by eliminating two other infrequently used tracks. Vehicle traffic data was collected continuously at the site for all movements over a threeday period, including counts and video tape. The railroad (BNSF) was a partner in the research, and provided data of all train traffic at the site for a typical seven-day period. Traffic Simulation Model Development The VISSIM traffic simulation model was used in the study for the following four reasons: (1) proven ability to model both train and vehicle traffic, (2) ability to model detailed traffic behavior, (3) ability to modify the model to incorporate intelligent transportation system (ITS) devices, and (4) proven ability to use hardware-in-the-loop (HIL) techniques to test traffic signal controllers. A VISSIM model was prepared for the study site, and was calibrated and validated using two different data sets extracted from the three days of traffic data. Development of the model was the major portion of the research effort, requiring significant study time and resources. Early Warning System An ideal EWS would have four characteristics: (1) simple and inexpensive to design, build, and install; (2) easily maintained by existing traffic signal technicians; (3) unilaterally controlled by the highway agency without need for any changes to the railroad control system; and (4) able to retain the time-tested safety aspects of the current at-grade crossing highway and railroad preemption control systems. The EWS developed for this research contains these four characteristics and uses four subsystems to provide (1) detection, (2) prediction, (3) congestion mitigation, and (4) safety. Conceptually two different types of sensor devices could be used for the detection subsystem: (1) Doppler radar and (2) time domain reflectometry (TDR). The Doppler radar detector has been used for train detection in previous research. It is pole-mounted in a fixed location adjacent to the railroad right-of-way, far from the at-grade crossing. It transmits data about a passing train through wireless transmission to the traffic signal controller cabinet, where a receiver ports the data to the small EWS field-hardened microprocessor computer that contains the other EWS subsystems. The TDR sensor was recently developed for a different train application as part of a Transportation Research Board (TRB) program for a different train application. It is undergoing field-testing and shows promise, but is as yet unproven for this application. The TDR unit induces an electrical pulse into the rails that travels outward until it encounters the wheels of an approaching train. A portion of the pulse is then reflected 3
back; the reflected pulse can be analyzed to provide the train's speed and distance. The TDR detector would be located at the crossing itself, and the data transmitted to the nearby traffic signal controller via hardwire or wireless. The EWS prediction subsystem uses an algorithm to predict the arrival time of the train and its passing duration based on the sensor data. Others have successfully used a simple algorithm, assuming a fixed speed. A fixed speed assumption is valid because the railroad companies strictly enforce train speed limits. The EWS congestion mitigation subsystem is the core of the research and it potentially could decide to take different actions, ranging from using different EWS parameters to aborting the use of the system because of uncertainty for that particular train. The model tested different parameters using an EWS algorithm developed for the study. The algorithm was written in the model's macro language, which required a significant effort to develop and refine. In addition, a third-party expert also was used to review the completed algorithm, which confirmed the accuracy of its logic and code. The algorithm does not impact the safety of the current, time-tested train premption control scheme. The algorithm always aborts when a train preemption signal is received. This is the same method currently used by NEMA-compliant traffic signal controllers to preempt the normal control sequence when a train arrives. The algorithm is designed to finish all of its operations just as the train preemption signal is received. However, even if it is not finished, the algorithm will always abort when the train preemption signal is received. Before/After Study Results Three measures-of-effectiveness (MOEs) were selected for evaluating the effects of the EWS: (1) delay, (2) travel time, and (3) queues. Of these, delay was the primary reporting MOE. Because of the tee intersection geometrics, two intersection movements (parameters) were available for receiving additional green time before the train arrived: (1) WB LT, which concurrently times WB TH and NB RT and (2) NB LT and NB RT, which time concurrently. The conflicting movements are WB LT, NB LT, and NB RT. Examining these two parameters while varying the other important factors of vehicle traffic flows, train traffic flows, MOE duration period, and train prediction errors, created substantially more cases than resources could accommodate. Therefore, only five cases were selected for testing the EWS. Two to six scenarios were modeled and tested for each case as well as the "no improvements" (before) scenario. Five major variables were studied by comparing results from the five cases and their multiple scenarios. Crossing gates downtime was varied at three levels: 4.5, 2.6, and 1.5 minutes, based on site train data. MOE results were analyzed at two levels: 15- and 30minute durations. Conflicting movement vehicle traffic was varied at three levels: actual, twice actual, and three times actual volume. The impact of train arrival prediction error was investigated at three arrival times: 25 seconds early, on-time, and 25 seconds late. Lastly, the impact of the parameters on the queue lengths was examined. From the perspective of the entire intersection, the overarching before/after results for this site are that the "costs" of the EWS outweigh the "benefits" when intersection delay is considered. The benefits are the savings in delay to the conflicting movements that 4
receive additional green time, while the costs are the increase in delay to the nonconflicting movements that are the donors of additional green time. Hardware-in-the-Loop Testing To test the EWS algorithm, a hardware-in-the-loop technique was used with a NEMA controller. This technique linked an actual NEMA controller containing the EWS algorithm to the traffic simulation model. The algorithm was implemented by linking four of the controller's built-in preemptors. The results verified that a microcomputer inside a traffic signal cabinet could send a signal to a standard NEMA controller that would then initiate the appropriate EWS algorithm routine. Conclusions and Recommendations Four generalizations appear to be supported by the study results, but more studies at other sites are needed to conclusively verify or dispute them. The first generalization is that the effectiveness of the Early Warning System is highly dependent on the site geometry, and on the vehicle and train traffic volumes. The relative volumes of individual intersection movements are critical because when a conflicting movement is given "extra" green time by the EWS before the arrival of a train, it "steals" that time from other movements. This complex, dynamic interplay is site dependent. The second generalization is that vehicles must be available to use the "extra" green time before the train arrives. This may not occur unless there were cycle failures before the train arrives. Without these cycle failures, there may not be enough vehicles in or nearing the queue to use the "extra" green time, especially when the "extra" green time is lengthy. The third generalization is that reducing long queue lengths for safety purposes may justify an increase in overall intersection delay. This may be especially true if the long queues are backing-up into nearby intersections or onto freeways. The fourth generalization is that the EWS may also be used in other ways to reduce congestion. One example is to send a warning signal to a DMS (dynamic message sign) that alerts drivers of a train's imminent arrival at the crossing so that they can take an alternate route. In conclusion, the EWS was ineffective for the study site, but two traffic characteristics may be confounding the results: (1) insufficient pre-train queue lengths for conflicting movements that limit their ability to utilize the "extra" green time; and (2) the lack of a single dominant conflicting flow at the intersection (the study site had fairly balanced cross-flows). Based on these lessons, a follow-up study is recommended at a new site with favorable geometry and traffic volumes. A multi-phase, incremental study approach should be used that allows termination of the study at the end of any phase that has clearly unfavorable results.
5
(blank)
6
1.
INTRODUCTION
1.1. MOTIVATION FOR RESEARCH Arizona's primary railroad system developed along the most accessible and constructible route alignments in advance of its primary highway system. Therefore, when a highway was developed, it was often placed parallel to the existing railroad tracks. The outlying suburban areas in Arizona use the primary highway system for trips to the urban areas for work, school, shopping, and recreation. The rapid growth of the urban areas in Arizona has caused suburban housing areas to be developed outward along highways leading into the urban areas. Where such highways are parallel to a railroad line, daily commuters on one side of the highway must cross these tracks to reach the highway. The highway is often the primary, and in some cases the only, route available to these commuters to reach the urban areas. These commuter at-grade crossings are typically the crossing of the railroad by the feeder road from the housing area to the highway, which may be a two-way, two-lane (TWTL) highway or a four- or more lane, limited access freeway. As the suburban area fills in, the feeder road--which usually begins as a TWTL road-may be upgraded to more lanes and become surrounded with commercial development. In the absence of a flyover structure (a roadway over- or underpass), the problems associated with at-grade crossings remain, and they typically will get worse as the volumes of vehicle and train traffic continue to increase. These commuter at-grade crossings cause congestion problems when the volume of traffic crossing the tracks is sufficiently large and/or the frequency of trains is sufficiently high. This is already occurring at various sites in Arizona and is destined to spread to more sites statewide. Continued growth in train traffic is predicted by the railroads and as Arizona's population continues to increase1, statewide vehicular traffic is also predicted to increase. Arizona's population is projected by the U.S. Census Bureau to
1
Arizona's statewide population has grown from approximately 1,300,000 in 1960 to 5,100,000 in 2000. The rates of growth each decade beginning with the 1960s through the 1990s are respectively 36%, 53%, 35%, and 40% per decade. During the same 40-year span, the PhoenixMesa metro area grew from approximately 725,000 to 3,250,000 and had rates of growth over the four decades of 43%, 54%, 40%, and 45% per decade. Tucson metro area grew from approximately 265,000 in 1960 to 845,000 in 2000 and had rates of growth from the 1960s through the 1990s of 32%, 51%, 25%, and 37%. Yuma metro's growth over this 40-year span was from approximately 46,000 to 160,000 and by decade, the growth rates were 32%, 49%, 18%, and 50% per decade. The Flagstaff metro area grew from approximately 45,000 in 1960 to 122,000 in 2000 and had rates of growth from the 1960s through the 1990s of 14%, 56%, 29%, and 20%. Nationwide from 1990 to 2000, Arizona ranked number 2, behind Nevada, as the fastest growing state by percent population growth. During this same period, Phoenix-Mesa metro area ranked as the 8th top metro growth area by percentage, Tucson ranked 37th, Yuma ranked 3rd, and Flagstaff ranked 69th (CensusScope 2000). Yavapai County, which includes the Prescott valley cities, had population growth from approximately 30,000 in 1960 to 170,000 in 2000 and experienced decade-by-decade growth rates of 27%, 86%, 58%, and 55% per decade over this 40-year span (Arizona Quicklinks 2005).
7
double from 2000 to 2030 from approximately 5.1 million to 10.7 million (State Interim Population Projections 2005). ADOT currently has 30 traffic signals on the state highway system that incorporate train preemption. Off the state system, the urban areas in Arizona maintain and control a significantly larger number of such traffic signals. Many of these operate under similar high vehicle and/or train traffic conditions, causing congestion problems. Additionally, these types of at-grade crossings cause safety problems when the roadway that crosses the railroad leads to/from a nearby signalized roadway intersection. This is usually the case. This specific type of at-grade crossing--the commuter at-grade crossing--is the focus of this research. The congestion and safety problems caused by these commuter at-grade crossings arise from a series of conditions that are briefly listed below and discussed in more detail later in this report. 1. When the roadway crossing the railroad leads to/from a nearby signalized roadway intersection, the right-of-way control systems for the railroad crossing and the roadway intersection act independently. These two control systems can act at cross-purposes to each other, causing safety problems. 2. The organizational and operating systems of the railroad company and the agency operating the traffic signals have evolved over time and resist change for safety and liability reasons. There currently is no technical or jurisdictional option available for the interactive management of the rights-of-way between the atgrade crossing and the roadway intersection. 3. The current method to mitigate the safety problems is for the railroad company to send a signal to the roadway agency when a train is approaching the crossing and another signal once the train has cleared the crossing. The roadway agency uses these signals to independently address the safety problems by altering its intersection control scheme in a manner known as train preemption (or simply preemption). 4. The current signalized roadway intersection train preemption control scheme's primary purpose is safety; congestion mitigation is a secondary goal. Congestion mitigation occurs only after the train has passed, in a reactive mode; none occurs in a proactive mode before the train arrives. 5. When the volumes of vehicles crossing the tracks are sufficiently large and/or when the duration and/or frequency of the passing trains is sufficiently high, the signalized intersection preemption traffic control scheme is insufficient to clear all of the vehicles. Therefore, the preemption control scheme delays the clearing of the congestion caused by a train passing for some period of time. 6. This delay in clearing the congestion, if sufficiently long, causes operational problems for the roadway system. Depending on the geometrics involved, when congestion is sufficient, queues of vehicles can back up long distances. The nearby intersection preemption control scheme reduces the possibility of these queues backing up into it. But other intersections, upstream and downstream from the nearby intersection and the railroad crossing, can experience queues backing up into them, causing safety problems. 8
The safety and congestion problems arising from these commuter at-grade highwayrailroad crossings are the focus of the research in this report and give rise to the research question that was investigated. 1.2. SCOPE OF THIS RESEARCH The primary objective of this study is to investigate these central issues: Research Question: Can solutions be applied at a signalized intersection, before a train passes a nearby at-grade highway-railroad crossing, that will mitigate the congestion that will occur after the train has passed? Furthermore, can this be accomplished using a standard traffic signal controller? In order to accomplish this, an initial research workplan was developed and approved by the project's Technical Advisory Committee (TAC). This workplan was modified during the progress of the research as guided by the unfolding results and unforeseen challenges encountered. The TAC also approved these modifications as they occurred. The final research workplan consisted of the following major tasks: 1. Review work by others that may be useful to this research. 2. Acquire major research equipment and modeling software needed to accomplish the work and train the research staff in its use. 3. Collect geometrics and traffic data at the selected study site. 4. Investigate a site-specific train arrival/prediction model. 5. Develop a microscopic traffic simulation model for the study site. 6. Develop an Early Warning System algorithm to apply congestion mitigation solutions before the train arrives. 7. Using the microscopic traffic simulation model and the EWS algorithm, test the research question using a series of variables and evaluate the results using a series of Measures of Effectiveness. 8. Using hardware-in-the-loop techniques, demonstrate the ability to implement the EWS algorithm using a standard NEMA traffic controller. The project was formally initiated in March 2003. The initial meeting with the project sponsors and technical advisors was held on May 1, 2003, at ADOT's district office in Flagstaff. The research was actively guided by a Technical Advisory Committee whose members are listed in Table 1. 1.3. ORGANIZATION OF THE REPORT The report is organized into chapters. Each chapter reports on an element of the research work. If additional detail is deemed relevant, it is included in an Appendix. The organization scheme for chapter topics and location focuses on understanding the outcomes rather than the chronological flow of work.
9
Table 1: Project 557: Technical Advisory Committee Members Ken Cooper Sam Elters Chuck Gillick John Harper Mike Lessard Ann Phillips George Wendt Tim Wolfe Gerry Craig Steven Hill David Wessel Dennis Roberts Debbie Casson ADOT, Roadway Standards ADOT, Kingman District Engineer ADOT, Northern Region Traffic Engineer ADOT, Flagstaff District Engineer ADOT, Traffic Engineering Group ADOT, Traffic Engineering Group ADOT, Office of Risk Management ADOT, Transportation Technology Group City of Flagstaff, Traffic Engineer City of Flagstaff, Traffic Signals Flagstaff Metropolitan Planning Organization City of Kingman, Community Development City of Kingman, Engineering Department
Mike McCallister BNSF Railway Company Dan Owsley Alan Hansen BNSF Railway Company Federal Highway Administration
As is typical with most research, many unanticipated challenges were encountered that were not envisioned in the workplan. However, unless these have a direct bearing on the results, they are not reported here. A detailed Table of Contents is given to assist the reader in finding topics of interest.
10
2.
PROBLEMS WITH AT-GRADE HIGHWAY-RAILROAD CROSSINGS
An at-grade highway-railroad crossing is one where a highway and railroad intersect on the same plane or grade. This is often simply termed as an "at-grade railroad crossing." A grade-separated crossing is one where a structure physically separates the two routes, either by the railroad going over the highway or the highway going over the railroad. An at-grade crossing causes a right-of-way conflict between the highway vehicular traffic and the railroad train traffic. This conflict is similar in concept to a regular intersection between two highways. Where two highways intersect, highway traffic control devices handle the right-of-way control: yield signs, stop signs, or traffic signals. Because a train requires a long distance and time to stop, vehicle traffic is always required to yield rightof-way at an at-grade railroad crossing to a passing train. An analogy using a typical intersection between two roads would be that the railroad acts as the mainline, which always has the right-of-way, and the highway acts as the side road, which has stop control. Stop control at a railroad crossing can be passive or active. Passive stop control is often the familiar "crossbuck" at the side of the road just before the track crossing plus various additional railroad crossing signs. Often, a typical highway stop or yield sign may also be present. Active stop control usually consists of flashing lights, or flashing lights with gates. In both passive and active control, the vehicular traffic is required to stop and the train is given the right-of-way. Typically, high volumes of vehicular traffic and/or train traffic at an at-grade railroad crossing dictates active stop control using flashing lights with gates. The first conceptual problem to arise at active control types of crossings is the split jurisdiction within the crossing. All of the railroad control is the jurisdiction of the railway company and all of the highway control is the jurisdiction of the governmental agency that owns the highway. Neither control system relinquishes control to the other system, so there is no technical or jurisdictional option available for an interactive management of the right-of-way at the crossing. What has evolved over time is a set of guidelines adopted by both groups' industry associations for active crossings. The basic conceptual methodology is that the railroad company's control system will send a signal to the highway agency's control system when a train is approaching the crossing and another signal once the train has cleared the crossing. 2.1. TRAIN SAFETY When a vehicle and a train collide, almost invariably the vehicle driver and occupants are injured, often fatally. The train engineer (driver) and train occupants are typically not injured due simply to the physics of the disparity in the mass of the two objects, although there are exceptions. Often, however, the train engineer is emotionally impacted and may be incapable of driving a train again. Typically a train cannot stop within sight distance of an at-grade crossing even when it locks its brakes. This means that when a train engineer first sees a vehicle stalled on the tracks and immediately hits the train brakes (and lays on the whistle), the engineer knows the he will not be able to stop in time but 11
has to watch as the fully-braking train approaches and then collides with the vehicle, finally coming to a complete stop at a considerable distance beyond the crossing. In addition to the emotional and possible physical injuries of train personnel, the train traffic on that track and possibly adjacent tracks is halted for a considerable period of time to clear and investigate the collision. Railroads often have little if any ability to route train traffic around the collision site causing all train traffic to come to a halt. The economic impacts of such disruptions on the railroad operations can be large. The railroad companies have vigorously promoted grade-separated crossings, active atgrade crossing control, and reduced numbers of at-grade crossings with passive control1. These efforts, aided by the governmental roadway jurisdictions involved, have helped to significantly reduced the number of at-grade crossing collisions over the last several years. For example, between 1990 and 2000, the national number of highway-railroad incidents decreased from 5,715 to 3,502 and the incident rate per million train-miles decreased from 9.39 to 4.84 (Federal Railroad Administration 2001). Additionally, the railroad companies have improved their active at-grade crossing control systems. The older, but still primary, method used by the railroad companies to gauge when to send a signal to the highway authority indicating that a train is approaching is to locate a sensor on the tracks at a fixed distance from the crossing. One drawback of this method is that the time between when the signal is sent and when the train reaches the crossing varies depending on the speed of the train. This is mostly mitigated because the railroads use strictly enforced train speed limits, however the train can go at a slower speed than the limit. The newer, improved method used by the railroads at some crossings provides the signal at a fixed amount of time before the train reaches the crossing, regardless of train speed. 2.2. VEHICLE SAFETY The right-of-way control system at the at-grade railroad crossing is installed and operated by the railroad company. At a passive control crossing, the signage is the only right-ofway control system although the train engineer uses his whistle to sound a warning as he approaches a crossing2. Additional signage may also be placed at the crossing by the authority that owns the roadway and/or the railroad company.
1
BNSF announced that in December 2003, it closed its 2,000th highway-rail grade crossing since the beginning of year 2000. During the four-year period from 2000 to 2003, BNSF closed six percent of its grade crossings, in a cooperative effort with landowners and communities along its route to identify unnecessary or redundant grade crossings. BNSF currently has approximately 30,000 at-grade crossings across its 32,500-mile rail network (BNSF Press Release 2004). In response to a legislative mandate, FRA has issued a Final Rule on the Use of Locomotive Horns at Highway-Rail Grade Crossings, which requires that locomotive horns be sounded as a warning to highway users at public highway-rail crossings. It takes effect on June 24, 2005; before that, the sounding of horns at public crossings was subject to applicable State laws and railroad rules. The final rule provides an opportunity, not available until now, for thousands of localities nationwide to mitigate the effects of train horn noise by establishing new "quiet zones." The rule also details actions communities with pre-existing "whistle bans" can take to preserve them (Federal Railroad Administration 2005-1).
2
12
At active control at-grade crossings, the railroad company is responsible for sensing the approaching train, activating the flashing lights (and gates, if applicable) in sufficient time to notify vehicle traffic not to enter the railroad crossing area until the train has passed. Once the train has passed, the railroad company is responsible for stopping the active warning system devices, which allows the vehicles to cross the railroad crossing. Typically an active at-grade railroad crossing control system is located in an urban area where the railroad is crossing through the urban area's roadway network. In this situation, active control systems are placed at those at-grade crossings that carry high vehicle and/or train traffic. Often the vehicle roadway crossing the railroad leads to/from a nearby intersection of two roadways. When the volume of vehicle traffic at this nearby intersection is sufficiently high, the intersection right-of-way will be controlled by a vehicle traffic signal control system. This traffic signal control system apportions the right-of-way to vehicles by giving each individual movement the right-of-way (green light) in rotation through a cycle, while simultaneously withholding the right-of-way from the other conflicting movements (red light). Therefore, a driver knows he has the right-of-way when he gets the green light and can safely proceed across the intersection. Problems arise when a roadway intersection is located near an at-grade railroad crossing because the railroad crossing control system and the roadway intersection control system act independently. An integrated control scheme cannot be used because neither of the two jurisdictions involved relinquishes control to the other. This causes two primary problems. The first is that when sufficient vehicles are waiting to get the green light on the roadway that crosses the railroad and leads to the roadway intersection, the queue that forms will back up across the at-grade railroad crossing. If a train approaches, these vehicles cannot move until they get the green light at the roadway intersection. The second problem is that while the train is passing, the roadway intersection traffic signal system continues to give vehicles the right-of-way to pass through the intersection toward the at-grade railroad crossing. When sufficient vehicles have done this the queue waiting at the at-grade crossing backs up into the roadway intersection. The method used to mitigate these problems is for the railroad company to send a signal to the roadway agency when a train is approaching the crossing and another signal once the train has cleared the crossing (Federal Highway Administration 2003). The roadway agency uses these signals as inputs to its roadway intersection traffic control scheme to trigger a special control scheme called preemption. Conceptually, once the signal of an approaching train is received, the normal rotation of the intersection right-of-way apportionment is interrupted (preempted) and vehicles that may be queued across the atgrade railroad crossing are given the green light to allow them to immediately clear the crossing. Then while the train is passing, the rotation of intersection right-of-way skips those movements that would allow vehicles to approach the train crossing, thereby reducing the likelihood of a queue backing up from the crossing into the intersection. When the signal is received that the train has passed, the right-of-way is first given to a designated movement(s) and then the intersection control scheme is returned to its normal rotation scheme of apportioning the right-of-way. Typically these designated movements are those that were skipped while the train was passing.
13
2.3. VEHICLE CONGESTION The roadway intersection located near an at-grade railroad crossing operates under the preemption traffic control scheme in response to the signals it receives from the railway company signaling the approach of a train and later the leaving of the crossing by the train. Once the signal is received that a train is approaching, the sole purpose of the preemption control scheme, both before the train arrives and as it passes, is the safety of the vehicles that might be placed in danger if the traffic control system was not aware of the approaching train. Once the signal is received that the train has cleared the at-grade crossing, the preemption traffic control scheme addresses the congestion that was caused by the train passing. The typical method is to give the right-of-way to those movements that wanted to cross the tracks, but were blocked from doing so while the train was passing. This scheme works reasonably well to clear the congestion caused by the passing train if the volumes of vehicles that are queued waiting for the train to pass are not too large. However, when these volumes are very large and/or when the frequency of the passing trains is very high, the preemption traffic control scheme is insufficient to clear these large volumes of vehicles. Therefore, the preemption control scheme delays for some period of time the clearing of the congestion caused by the train passing. This delay, if sufficiently long, causes operational problems for the roadway system that the roadway jurisdiction(s) try to address in various ways. Depending on the geometrics involved, when congestion is sufficient, queues of vehicles can back up long distances. The nearby intersection preemption control scheme reduces the possibility of these queues backing up into it. But other intersections, upstream and downstream from the nearby intersection and the railroad crossing, can experience queues backing up into them causing severe safety problems. One way to address these safety and congestion problems is to eliminate the at-grade crossing by creating a grade-separated crossing, also called a "flyover." Often this is the preferred method but this solution is very expensive. Additionally, when the railroad is crossing several roadways in an urban roadway network several flyovers may be required. In this situation an area-wide scheme is preferred. This scheme typically designates two or more railroad crossings for flyovers and closes the other crossings.
14
3.
SITE SELECTION, GEOMETRICS, AND TRAFFIC
3.1. SELECTION OF THE STUDY SITE The investigation of the research question required the selection of an actual site that was experiencing the requisite conditions. Recall that commuter at-grade crossings are defined as having these characteristics: 1. A roadway and railroad intersect on the same plane or grade. 2. The roadway crossing the railroad leads to/from a nearby signalized roadway intersection. 3. Traffic crossing the at-grade highway-railroad crossing have one or more of these characteristics that occur more-or-less concurrently for recurring periods during a year, typically during weekday vehicle AM and/or PM peak periods: a. Vehicle traffic volume is large. b. Train frequency is high. c. Duration the crossing is closed to allow a train(s) to pass is long; this is a function of train length, speed, number of tracks, and frequency of trains. The term "commuter" is applied to the term "commuter at-grade crossings" because usually the high volume of vehicle traffic is primarily attributed to drivers making hometo-work trips or work-to-home trips. Traffic engineers call these the AM peak period and the PM peak period. Another requirement for a study site was that it be within the jurisdiction of the Arizona Department of Transportation (ADOT). This meant that a state highway had to be crossed at-grade by the railroad (atypical) and/or that the highway was part of the nearby signalized intersection (typical). The potential study site location was further refined when a secondary sponsor for the research joined the study, the City of Flagstaff. One potential site that satisfied both ADOT and the City was the intersection of Route 66 and Enterprise Road. The north-south leg of this intersection (Enterprise) was crossed at-grade by the Burlington Northern and Santa Fe (BNSF) Railway's double mainline tracks. The Enterprise Road crossing is located approximately 75 feet south of the intersection. Additionally, the BNSF also has parallel spur and siding tracks at this crossing for a total of 4 tracks, however the train traffic of interest all occurs on the double-track mainline (see Figure 1). 3.1.1. Railroad Equipment and Operations Used at the Site "The Federal Railroad Administration was created by the Department of Transportation Act of 1966 (49 U.S.C. 103, Section 3(e)(1)). The purpose of FRA is to: promulgate and enforce rail safety regulations; administer railroad assistance programs; conduct research and development in support of improved railroad safety and national rail transportation policy; provide for the rehabilitation of Northeast Corridor rail passenger service; and consolidate government support of rail transportation activities." (Federal Railroad Administration 2005-2)
15
The Secretary of the Department of Transportation has authority over both the Federal Railroad Administration and the Federal Highway Administration (FHWA), the two primary regulatory groups over railroads and highways. State Law governs highwayrailroad crossings but typically a State adopts the standards, with modifications to fit state needs, as codified in the Manual on Uniform Traffic Control Devices (MUTCD - Federal Highway Administration 2003). Arizona has adopted the MUTCD, with modification, but none of the modifications significantly alter the standards in the MUTCD that govern at-grade crossings.
Figure 1: Aerial Photos Of The Study Site The left photo shows the area surrounding the study site. The study site includes the atgrade crossing of Enterprise Road with the BNSF tracks, and the Route 66/Enterprise "Tee" intersection just to the north of the at-grade crossing. Route 66 and the BNSF Railroad mainline tracks run parallel. The photo at right is a close-up of the study site. Railway companies own and maintain the tracks, and generally own the property (rightsof-way) to either side of the tracks. At at-grade crossings, they generally install and maintain the tracks, the roadway surface between and around the rails, and traffic control devices on their rights-of-way. While the railway owns the track, the roadway at a crossing is typically owned by a government agency. This roadway agency maintains the road approaching the crossing on either side of tracks. The Federal Highway Administration is responsible for public grade crossing issues that affect highway safety. FHWA, through the MUTCD, provides guidelines and standards 16
for the correct design of grade crossings, the assessment of safety at a grade crossing, and appropriate placement of traffic control devices at and on the approach to a grade crossing. These traffic control devices at the study site include circular advance warning signs, crossbucks (the familiar X-shaped signs), pavement markings, and bells, gates, and flashing lights as shown in Figure 2 (Federal Railroad Administration-3, 2005).
Figure 2: Photo Of The At-Grade Crossing At The Study Site Study site looking south from the Route 66 and EnterpriseRd.intersection to the at-grade highway-railroad crossing. The northbound vehicles on Enterprise Rd., facing the viewer, and the lone southbound vehicle are waiting behind lowered gates as a train passes. All of the red lights on the gates, crossbucks, and overhead gantries are flashing. Since both the railway company and the roadway agency maintain jurisdiction and responsibility for safety in their own rights-of-way, an at-grade crossing represents the unique condition wherein both have some responsibilities for a common portion of land. Technically, however, the land at the crossing is owned by the railway company and at an active control crossing, they manage and operate the control system and appurtenances involving the crossing itself. This control system is complex and must be compatible with the control systems that the railway company uses to manage its facilities and dayto-day operations up and down the line (see Figure 3). For purposes of this report, it is sufficient to conceptually describe the railway's control system at the crossing and include only those parts that affect the vehicles operating on the roadway. At the study site, the BNSF Railway Company is responsible for sensing the approaching train and activating the flashing lights and gates in sufficient time to notify vehicle traffic not to enter the railroad crossing area until the train has passed. Once the train has passed, BNSF is responsible for stopping the active warning system devices, which allows the vehicles to cross the railroad crossing.
17
Figure 3: Photo Of At-Grade Crossing Equipment At The Study Site Looking east across the at-grade crossing showing the primary active crossing gates and warning lights. The nearside vehicle has just exited the Route 66 and Enterprise Rd. intersection and is heading southbound on Enterprise Rd. The far vehicle is heading northbound toward the intersection. ADOT manages and operates the control system of the Route 66 and Enterprise Road intersection that lies approximately 75 feet north of the at-grade crossing. Neither the BNSF at-grade control system nor the ADOT signalized intersection control system relinquishes control of its system to the other during the passing of a train. They operate independently, which precludes a joint, interactive control scheme. In order to allow the intersection control system to modify its control scheme during the passing of a train, the standard method (Federal Highway Administration 2003) used nationally is for the railway company to notify the roadway agency. Conceptually the railway crossing system notifies the intersection control system by sending a signal to the roadway agency 18
when a train is approaching the crossing and another signal once the train has cleared the crossing1. At the study site, BNSF operates an advanced type of detection system. This system can provide a signal at a constant time interval before the train arrives rather than at a constant distance from the crossing. ADOT and BNSF have agreed on this constant notification time interval. The constant time interval has a small variance but during an intensive data collection period at the site, the predicted time to crossing was typically within +/- 1 second2. The BNSF detection system calculates the speed of the train and predicts the time of arrival at the crossing. It waits until the constant notification time interval remains and then sends the signal to ADOT. ADOT uses this signal to interrupt its normal operation of the traffic control signal to transfer control to a special control mode of operation called preemption. During preemption, the normal sequence of traffic control signal indications are interrupted to avoid entrapment of vehicles on the highway-rail grade crossing by conflicting aspects of the intersection traffic control signals and the highway-rail grade crossing flashing-light signals and gates. 3.1.2. Traffic Signal Equipment and Operations Used at the Site ADOT manages and operates its intersection traffic control signals in accordance with the MUTCD, as modified for the State of Arizona, including its preemption control mode for at-grade crossings (Traffic Group 2005). At the study site, ADOT uses a NEMA controller3 and cabinet.
1
The MUTCD specifies a fail-safe type of communications method from the railroad control system to the roadway intersection control system. The preemption feature shall have an electrical circuit of the closed-circuit principle, or a supervised communication circuit between the control circuits of the highway-rail grade crossing warning system and the traffic control signal controller. The traffic control signal controller preemptor shall be activated via the supervised communication circuit or the electrical circuit that is normally energized by the control circuits of the highway-rail grade crossing warning system. The approach of a train to a highway-rail atgrade crossing shall de-energize the electrical circuit or activate the supervised communication circuit, which in turn shall activate the traffic control signal controller preemptor. This shall establish and maintain the preemption condition during the time the highway-rail at-grade crossing warning system is activated, except that when crossing gates exist, the preemption condition shall be maintained until the crossing gates are energized to start their upward movement. When multiple or successive preemptions occur, train activation shall receive first priority. (Federal Highway Administration 2003) BNSF gathered information continuously from its crossing equipment recording devices at the study site in support of this study for a 7-day period from 4/26/04 to 5/3/04. At the study site intersection, ADOT uses a NEMA Econolite ASC/2S-2100 controller (Econolite Control Products, Inc. 2005). This is a TS2, Type 2 controller operating in the TS1 environment in a Type 1 Cabinet. ADOT uses an extra Econolite board within the controller to handle its preemption communications and uses the D Plug for all input and output preemptor calls.
2
3
19
ADOT's typical practice for its preemption mode is used at the study site and conceptually consists of the following sequence of events. Specifics given all refer to the study site4: 1. Receive the preemption signal from the railroad (BNSF) that indicates the train is approaching the site. 2. Immediately go to the Preemption Track Clearance (TC) Phases (NB LT and NB RT at the study site). a. The designated Preemption TC Phases under ADOT's typical procedures are those movements that potentially can be queued up across the railroad tracks waiting for a green light. (At the study site, these are the NB LT and NB RT movements. Since the intersection is a "tee" intersection, there is no SB leg, which means there are no NB TH, WB RT, or EB LT movements and, of course, no SB movements of any kind.) b. If the green is timing a movement(s) other than the Preemption TC Phases when the preemption signal is received, then this movement(s) will be ended. It will be ended in a safe manner, which means that it will be given a designated preemption minimum amount of green (5 seconds at the study site), followed by a yellow (change interval) and an all-red (clearance interval). These yellow and all-red intervals can be designated specifically for preemption or they can be allowed to default to those used during normal operations (yellow and all-red times used in normal operations are used at the study site). If the minimum amount of green has already elapsed when the preemption signal is received, the movement(s) will immediately proceed to its yellow and all-red. c. If the green is already timing for the movement(s) designated as the Preemption TC Phases, then this movement(s) will continue for the designated length of TC Green time interval, which commences when the preemption signal is received. d. Once the Preemption TC Phases have started timing their green, they will continue in green until the designated TC Green time interval has elapsed. e. Once the TC Green time interval has elapsed, a yellow and an all-red interval will follow. These intervals can be designated as the TC Yellow and TC All-Red intervals or they can be allowed to default to those used
4
The nomenclature used throughout this report describing the movements of traffic through an intersection are from the perspective of the direction of traffic. For example, a vehicle that is on the south side of an intersection and traveling north toward the intersection is a NB (northbound) vehicle. This is further refined by designating the direction the vehicle intends to go after it leaves the intersection, e.g., NB LT (northbound left-turn), which could also be called NB to WB (northbound to westbound). In this report, the NB LT type of designation is used. So when a group of vehicles are described as NB, the group includes all vehicles that intend to go NB LT, NB TH (northbound through) and NB RT (northbound right-turn). Similar terms are used for WB (westbound), SB (southbound), and EB (eastbound).
20
during normal operations (the yellow and all-red times used in normal operations are used at the study site). 3. Go to Preemption Hold Phases (WB TH and EB TH at the study site). These are phases that do not conflict with the passing train. Train conflicting phases are those that would direct vehicles toward the at-grade railroad crossing or away from it while the train is passing (WB LT, EB RT, NB LT, and NB RT at the study site). If any of the Preemption Hold Phases need to be run separately from each other, they will be run in their normal operations sequence, while omitting the train conflicting phases from the sequence. (At the study site the Preemption Hold Phases (WB TH and EB TH) do not conflict with each other so they run simultaneously.) This will continue until the railroad (BNSF) sends the signal indicating the train has left the crossing. a. To insure safe operations, a Minimum Hold Time is designated. This minimum time must be satisfied in addition to receiving the signal from the railroad that the train has left the crossing before control can proceed to the Preemption Exit Phases. 4. Go to Preemption Exit Phases (NB LT and NB RT at the study site) and return to normal operations. Since the signal has returned to its normal operations, these Preemption Exit Phases time their green, yellow, and all-red intervals using their normal operations intervals. a. Preemption Calls are also placed on any movement(s) desired (WB LT and WB TH at the study site) as control is returned to normal operations. The normal sequence of movements used in normal operation is observed so the movement(s) that is normally called after the Preemption Exit Phases has finished is what runs next. What the Preemption Calls do is to ensure that the movements that were called will be serviced even if they don't have any vehicles waiting. (For the study site, the normal sequence serves the WB LT and WB TH movements (the Preemption Exit Calls at the study site) after the NB LT and NB RT movements (the Preemption Exit Phases at the site) have run.) The signal heads are located on overhead cantilevered arms and on the uprights to these arms. There are also two pedestrian crossings: east-west on the south side of the intersection and north-south on the east side of the intersection. These have low pedestrian traffic (see Figure 4).
21
Figure 4: Photo Of The Intersection At The Study Site Looking south at the study intersection, which is a "Tee," the missing leg being on the north side, from where the photo is taken. The intersection signal lights are controlled with a NEMA controller, and signal heads are mounted on side and overhead poles. Route 66 is the east-west roadway running left-to-right in the foreground of the photo. The at-grade railroad crossing can be seen in the background, crossing Enterprise Road.
3.2. SITE GEOMETRICS AND MODIFICATIONS FOR MODEL 3.2.1. Current Geometrics at the Study Site The study site is the intersection of Route 66 and Enterprise Road in Flagstaff, Arizona. The intersection serves both commuters and tourists as well as commercial vehicular traffic. Although the intersection has four legs, the fourth leg on the north side of the intersection is a driveway into a vacant city-owned lot. There are no traffic signal heads servicing this leg, i.e., SB traffic. Therefore, the intersection is functionally a Tee intersection. This intersection was significantly improved to its current configuration approximately three years before the study began. The other three legs service significant volumes of vehicular traffic. The EB and WB movements are on Route 66. The normal cross section for Route 66 is five lanes, with two through lanes in each direction and a center common left-turn lane. Both EB and WB directions have two lanes for through movements. EB has a single right turn lane and a long storage lane. WB direction has a single dedicated left turn lane that is essentially of unlimited length due to the center common left-turn lane. Both the WB LT and the EB RT movements lead traffic into Enterprise Road and across the railroad tracks, which are located approximately 75 feet south of the intersection. Enterprise Road is a north-south connector road that services traffic between the study intersection and the intersection of Butler Avenue and Huntington Road, which lies approximately 800 feet to the south. NB Enterprise Road begins at the intersection of Butler Avenue and Huntington Drive as two lanes. A merging single slip lane from Huntington Drive quickly joins it. As it approaches the study intersection, it widens into a four-lane section containing dual left turn (LT) lanes, a hatched auxiliary lane and one right turn (RT) lane. The dual LT lanes lead vehicles into westbound (WB) Route 66 while the RT lane leads into eastbound Route 66. The southbound Enterprise movement 22
leaves the study intersection with two lanes. There is approximately a 60-foot storage length between the northbound (NB) stop bar and the railroad crossing. Route 66 and Enterprise Road have sidewalks on both sides but pedestrian traffic is low. Pedestrian crossings at the study intersection are limited to two: a north-south crossing on the east side and an east-west crossing on the south side. 3.2.2. Modified Tee Intersection Geometrics Used for the Study The study intersection had significant congestion problems before it was improved in 2002-2003. These problems were substantially reduced by the geometric improvements. Additionally, the close coupling of the two intersections at each end of the Enterprise Road connector caused them to interact with each other, although the timing of their signals is not coordinated. Substantial efforts were spent modeling the current configuration of the two closecoupled intersections. The modeling software used in the study is VISSIM, which is described in detail in Chapter 4. Models were developed using current vehicle traffic through these intersections. The Early Warning System was initially tested using this configuration. Significant problems developed because of the complexities that occur at the site. It was discovered that while this site qualified as a commuter at-grade crossing, its complexity made it difficult for these reasons: The geometric improvements to Route 66/Enterprise Road had already reduced a significant portion of the congestion the EWS was designed to alleviate. The close coupling of the two intersections caused an interaction that was most probably confounding results. The site was atypical of the site the EWS was designed to help. A typical site would have a feeder road leading across an at-grade crossing to join a main highway. The traffic on the feeder road would be to/from an isolated residential area. The study site consists of two arterials, Route 66 and Butler Avenue, that parallel the railroad tracks on either side. These are cross-connected infrequently, but when they are, significant traffic is exchanged between them. This causes the study intersection to have strong movements in several directions rather than the anticipated primary strong movement to/from a residential area with AM and PM peaks. It was agreed with the project TAC to attempt to overcome some of these difficulties by modeling a modification of the study site. This modification was used for all testing and results, except traffic volumes were modified in some test cases as described later. Therefore, the modeled study site had these characteristics: 1. Pre-improvement geometrics: The intersection and at-grade crossing geometrics were modeled using the pre-improvement geometrics. The only improvement on the east-west Route 66 route was to the EB RT storage lane, which was shortened to 360 feet. Enterprise Road had several changes that reduced the cross section at the intersection to one SB lane and two NB lanes, one a LT and the other a RT lane.
23
2. Simplified at-grade railroad configuration: The current crossing has four tracks: dual mainline tracks, and spur and siding tracks. The spur and siding tracks were eliminated. The dual mainline track was modeled as a single track and the length of a single "long" train was used to simulate the simultaneous crossing of two trains in opposite directions. 3. Eliminated the second close-coupled intersection: The proximity of the second intersection, Butler/Enterprise, caused a "pumping" action that directed traffic at the study intersection in a patterned, but unpredictable way. Additionally, NB Enterprise traffic that might otherwise queue behind the crossing while a train was passing would be interfered with by the needs to keep the Butler/Enterprise intersection clear. However, this varied unpredictably, depending on driver behavior. Therefore, the study intersection was modeled without the Butler/Enterprise intersection. Furthermore, Enterprise was modeled with sufficient length that all queuing traffic was accommodated. While these modifications did not completely convert the study intersection into the typical commuter at-grade crossing envisioned in the research question, it was a useful compromise. This allowed the real traffic that had been captured at the site and used to calibrate and validate the model to be applied to the modified tee geometrics. This was an important benefit and the alternative was to model both an artificial intersection and artificial traffic. Whereas the artificial intersection would have been much closer to the commuter at-grade crossing envisioned by the research question, the use of artificial traffic would make it difficult to generalize the results to potential field test sites. 3.3. VEHICLE TRAFFIC USED IN THE MODEL Collecting vehicle traffic at the study site and extracting that needed for modeling was not a trivial task. Three groups were used to collect data on the traffic moving through the two intersections: one to record the traffic counts, one to simultaneously videotape intersection movements, and AZTrans supervisory staff. Data was collected for three days from Wednesday, April 23, 2003, through Friday, April 25, 2003. 3.3.1. Data Collection Procedure AZTrans, in conjunction with Traffic Data Systems (TDS), collected vehicle volume data at the intersections of Route 66 and Enterprise Road, and of Butler Avenue/Enterprise Road and Huntington Drive (see Figure 5). TDS used forty pneumatic hoses to collect 24-hour traffic volume data for three days, beginning 12:00 a.m., Wednesday, April 23, 2003, and ending 11:55 p.m., Friday, April 25, 2003. These tubes consisted of either stubs (tubes extending only to "drip line" of vehicle) or full lane tubes (tubes extending the full length of the lanes being counted). Stubs were used to record the right turn movement on WB Butler and full lane tubes were used in all other lanes. In order to collect data on internal lanes (for example, the innermost lane in a dual left-turn lane within a five-lane section), TDS "jammed" the part of the tube that extended over the outermost lanes, thus collecting data for only the innermost lane.
24
Figure 5: Vehicle Traffic Data Collection Using Pneumatic Hoses Looking east at the approaching WB Route 66 traffic at the study intersection of Route 66 and Enterprise Road. Two pneumatic hoses are in place across three lanes of traffic between the two white arrows. One hose spans the two WB TH lanes. The second hose spans all three lanes but is "jammed" for the portion that crosses the two WB TH lanes so it is only recording traffic on the WB LT lane. The recorder box is located behind a small pine tree to the left of the left arrow. Forty pneumatic hoses were used at the study intersection and the nearby intersection of Enterprise Road at Butler Ave. to capture all of the needed traffic flow data over a three-day period.
Additional double pneumatic hoses were placed at three locations: NB Enterprise (north of the Butler-Enterprise intersection and south of the Huntington cutoff), SB Enterprise (south of the Route 66-Enterprise intersection and north of the Butler-Enterprise intersection), and EB Butler (east of the Butler-Enterprise intersection), which collected data on vehicular volume, class, and speed. This field data was used as the benchmark for calibration and validation purposes in the VISSIM model. TDS checked the recording boxes daily to insure proper operation. One box, recording WB Butler at the Enterprise/Butler intersection, failed on Wednesday morning so the missing data was recollected at this location the following week during the same day and time. Five camcorders recorded queue lengths from the following three locations: Route 66/Enteprise intersection (Station 1), McDonald's Restaurant rooftop (Station 2), and 25
south of the Butler/Enterprise intersection (Station 3). These locations are shown on a map in Figure 6. Station 1, the Route 66 and Enterprise intersection, recorded vehicle queues on EB and WB Route 66. Two wide-angle lens cameras were used to record this vehicle footage at this site. Station 2, from the rooftop of the McDonald's fast food restaurant, captured footage of vehicle queues on EB Butler. Station 3, which was just south of the Butler/Enterprise intersection, recorded queue data on WB Butler, SB Enterprise and SB Huntington. Camcorder locations at both intersections used "scissor lifts" to elevate the camera platforms above the intersections, 10 feet at Station 1 and 25 feet at Station 3. Traffic footage was collected for 9 hours on Wednesday and Friday and 12 hours on Thursday. The 9 hours recorded are 6:30 a.m. to 9:30 a.m., 11:30 a.m. to 2:30 p.m., and 4:00 p.m. to 7:00 p.m. Mini-DV tapes were used and switched out every 60 minutes, except for Wednesday, when one camcorder utilized 40-minute tapes. Five NAU student research assistants from AZTrans and four cameramen from Echo Productions and Bold Eagle were hired to man the cameras in shifts, with supervisory staff from AZTrans available onsite for direction (see Figure 7). 3.3.2. Adjustments made to data provided by TDS Data from the field was organized into a Microsoft EXCEL spreadsheet and aggregated into five-minute totals by TDS and provided to AZTrans. These five-minute aggregations listed vehicle counts for nineteen stations plus eleven additional stations with vehicle counts, speeds, and tire configuration for three days of data collection. Using this dataset, AZTrans developed heavy vehicle adjustment factors for each fiveminute period. After applying the heavy vehicle factor to the data, each five-minute period vehicle count was converted to a flow rate (veh/hr). This vehicle flow rate data was entered into the VISSIM model for nineteen movements and five entry points into the network.
26
Station 1
Station 2
Station 3
Figure 6: Video Cameras Location Map Map shows locations of the three video camera stations used to record traffic flow data over the same three-day period that pneumatic hose data was collected. Stations 1 and 3 are located on "scissor lift" platforms, and each uses two cameras. Station 2 uses a single camera located on the roof of a McDonald's restaurant. 27
Figure 7: "Scissor Lifts" Aided In Obtaining Adequate Video Top photo is taken from on top of the McDonalds restaurant, at video camera Station 2, looking west across the Butler Ave--Enterprise Street intersection. The red arrow shows the location of video camera Station 3, which is also shown in the lower right photo. The lower left photo is looking south from the Route 66--Enterprise Road intersection, showing video camera Station 1 in the foreground.
3.3.3. Data Used in the VISSIM Model for Calibration and Validation AZTrans developed the VISSIM model using the existing geometry with improvements and the volumes obtained from the traffic data collection program. Appropriate time periods were extracted from the data that best represented the desired conditions at the study site. The primary conditions desired were peak vehicle traffic flow coupled with railroad crossing preemption(s) during the same time period. The initial model was developed for the time period from 8:10 a.m. to 9:20 a.m. on Friday, April 25, 2003, for calibration purposes.
28
In the developing of the VISSIM model, significant data was required beyond vehicular vehicle flows. These included vehicle speed distribution(s), vehicle type(s), routing decisions, and priority rules. Routing decisions are those routes placed in the traffic network that "lead" individual vehicles to their destination, typically through an intersection. Priority rules are used to establish right-of-way for conflicting movements. They are generally used for turning movements, stop signs, and places where vehicles merge. Vehicle speed distributions were set per observed field data, ranging from 25 mph to 40 mph, with the 85th percentile traveling at a set desired speed. Vehicle classes used in the VISSIM modeling program were identified in European terms. VISSIM is international modeling software originally developed in Germany and several of the terms used in the software reflect European terminology rather than American terminology, however, the functionality is the same (Planung Transport Verkehr AG, 2003). Passenger car types were Car 1 through Car 6 with approximate lengths of 14 feet; Sport Utility Vehicles/Trucks had lengths between 16 and 19 feet; and HGV (Heavy Goods Vehicle) had lengths between 28 and 60 feet. Cars were specified separately from Sport Utility Vehicles/Trucks so that different lengths and color identification could be entered with ease. HGV vehicle types include all heavy vehicles, including buses, that traverse the traffic network. Pedestrian and bicycle movements were omitted from the model because their volumes were insignificant. Other entered data included speed reduction zones, which were used to replicate speed conditions present in the field. Speed reduction zones were placed in all turning movements at the two intersections where short sections of low speed are typical, such as turning lanes and curves. According to the VISSIM 3.70 User's Manual, "When approaching a reduced speed area, a vehicle reduces its speed in order to reach its new (slower) speed at the beginning of the reduced speed area. The deceleration process is initiated according to the deceleration value defined. The acceleration at the end of the reduced speed area is determined by the characteristics of the driver-vehicle-unit as well as the original desired speed" (Planung Transport Verkehr AG, 2003, pp. 4-35). Turning movement speeds ranged between 5 and 26 miles per hour, depending on the type of vehicle making the turn. The Arizona Department of Transportation and the City of Flagstaff provided timing information for the signals in the traffic network. ADOT operates and maintains the signal at the intersection of Route 66 and Enterprise Road while the signal at Butler Avenue/Enterprise Road/Huntington Drive is owned and operated by the City of Flagstaff. This timing information, including normal train preemption, was entered into the VISSIM model. The intersection of Route 66 and Enterprise Road operates as an actuated uncoordinated intersection. Only one overlap is incorporated at this intersection and operates with both Route 66 WB LT and Enterprise NB LT. The Enterprise NB RT (Movement 8) never runs as a stand-alone phase and operates solely as an overlap. The movements and their phase numbering scheme are shown in Figure 8. Also the in-road detector information was entered for both intersections. Detector information was obtained both from field observations and information provided by the City of Flagstaff.
29
Route 66 (E-W)
WB TH (6) WB LT (1)
EB TH (2) EB RT (na)
N
NB LT (3) NB RT (8)
Enterprise (N-S)
Figure 8: Study Intersection With Vehicle Movement Controller Numbers The intersection movements are labeled as to direction including their controller movement (phase) number. For example, Northbound Right Turn is movement number 8. EB RT is labeled "na" because while it has an exclusive lane, it doesn't have a dedicated control phase so it moves concurrently with EB TH (2). 3.3.4. Modified Data Used in the VISSIM Model for Study Cases As discussed earlier, the two intersections as they exist today were unsatisfactory for study purposes and were modified for the modeling. The modified Tee intersection geometrics used for the study also required modifications to the vehicle data. The vehicular volume data used in the modified Tee intersection VISSIM model reflects the time from 3:00 p.m. to 6:00 p.m. at the study site. This time represents observed peak hours occurring during the three-day period of data collection. The volumes used in the modified Tee model were obtained by averaging the vehicular volume data collected from Wednesday through Friday, 3:00 p.m. to 6:00 p.m., so as to obtain a representative peak period. A peak hour factor adjustment of 0.984417 was developed from the classification data and was applied to the raw data to obtain the final volumes used in the model. 3.4. RAILROAD TRAIN CHARACTERISTICS USED IN THE MODEL The congestion experienced by the passing of a train is a function of four primary variables: The volume of vehicle traffic crossing the railroad. The volume of vehicle traffic using the nearby signalized intersection.
30
The duration of railroad crossing gates-down. The headway5 between trains. Data was collected by BNSF for a week of all train activity at the study site. The longest duration of a gates-down condition for modeling the site was established at 4.5 minutes (270 seconds), which represents 95% cumulative probability, i.e., the probability that 95% of all gates-down durations will be of this length or less. Similar values were established for the shortest and average gates-down durations of 1.5 minutes (5% cumulative probability) and 2.6 minutes (50% cumulative probability) respectively. In this report, the term "longest" train actually means the longest gates-down duration caused by a train. Similar meanings apply for the "shortest" train and "average" train. At the double-track study crossing, the "longest train" is actually two trains that cross in opposite directions. The first to cross has not cleared the crossing before the second train starts to cross. Therefore, the gates stay down continuously until both trains have cleared the crossing. While the headway between trains also effects congestion, it is a more difficult variable to quantify. While this data was collected and analyzed at the study site, its use presents difficulties when coupling with a gates-down duration. For example, it would be a rare event if the longest train was followed by the shortest headway of the next train6. While these compound probabilities could possibly have been established by collecting more data, it was decided that this would only add complexity to the modeling that wasn't useful. Studying the impacts of a single train passing at peak hour conditions was selected as the condition of most interest, and this study is limited to that focus. Detailed statistics and cumulative distribution functions of the railroad headway and gates-down durations are provided in APPENDIX B.
5
Headway is the time between successive vehicles (trains), typically measured from the front of the leading vehicle to the front of the following vehicle in seconds. What impacts vehicle congestion is the duration of the "gates-down" in combination with the interval until the next "gates-down." Since the study site is a dual mainline track, an initial "gatesdown" duration is caused by a train traveling in one direction. The subsequent "gates-down" duration is caused by a train traveling in either the opposite direction or the same direction. If the train is traveling in the opposite direction on the parallel track, it could arrive at any time during or after the previous train is at the crossing. If it is traveling in the same direction, on the same track, it is limited by the railway company's control system that governs the flow of train traffic in the same direction on the same track. This is a complex system but conceptually it sets an approximate minimum following headway between trains, which can vary depending on the railroad geometry and crossing control system at the crossing.
6
31
(blank)
32
4.
MODEL DEVELOPMENT
4.1. SELECTION OF THE MODELING ENVIRONMENT The overarching reason to use a model to test the research question is the liabilities associated with direct field-testing. If field-testing were to be performed as the first step of a research investigating changes in intersection traffic control, it would have to be on a trial-and-error basis. Obviously, safety and congestion issues preclude such an approach. For these reasons, researchers use models to test proposed changes, especially new ones, before any field-testing is even contemplated. Models can be classified in many ways (TRB HCM, 2000, pp. 31-1 to 31-6). One is to vary three dimensions: (a) scale of detail, (b) basis of analysis, and (c) method of analysis. Scale of detail is categorized into (1) large scale, that requires highly aggregated data, (2) small scale, that requires extensive disaggregate data, and (3) middle scale, which is somewhere in between as to the amount of data required. These model scales are called respectively macroscopic, microscopic, and mesoscopic. The basis of analysis can be categorized as (1) theoretical or (2) empirical. And the method of analysis can be categorized as (1) deterministic or (2) stochastic. It is important to realize that ways of classifying models are not typically an "either-or" situation as much as somewhere along a multi-dimensional continuum (Akcelik & Associates, 2005). For the purposes of exploring the research question, the parameters to be varied and tested require a high degree of detail at a microscopic level. The modeling environment has to be able to extract measures of effectiveness. Due to the variability of both the vehicle and train traffic, a stochastic modeling approach would serve best, in the form of simulation. Most traffic models have elements of both traffic flow/driver behavior theory and reliance on empirical analysis of measured traffic site data for some modeled characteristics. A microscopic traffic simulation modeling environment was chosen for use in this study. "With advances in computing technology and the ever-increasing power of personal computers, many sophisticated stochastic microscopic simulation models have been developed in the area of transportation engineering. Improved user interfaces have significantly reduced the effort needed to code and interpret the results of these simulations models. As a result, more traffic engineers are relying on microscopic simulation models to analyze complex transportation problems when analytical methods cannot provide satisfactory solutions." (Tian, et al, 2002, p. 23) A handful of microscopic traffic simulation modeling environments are available for use and have been carefully examined by the research community. Of these, VISSIM was chosen for four primary reasons: (1) high control over the vehicle-level parameters, (2) ability to use a powerful macro language to program the EWS features, (3) proven ability to use hardware-in-the loop, and (4) an update resolution of several times per second. 4.2. VISSIM MODEL CALIBRATION "Calibration is necessary because no single model can be expected to be equally accurate for all possible traffic conditions. Even the most detailed microsimulation model still 33
contains only a portion of all of the variables that affect real-world traffic conditions. Since no single model can include the whole universe of variables, every model must be adapted to local conditions. ... The objective of calibration is to improve the ability of the model to accurately reproduce local traffic conditions." (Dowling, Skabardonis, and Alexiadis, 2004) The VISSIM model was calibrated using the current existing geometric configuration at the intersection and the collected data as described in Chapter 3. The collected data from the field served as the benchmark for the calibration process. In order to represent normal traffic conditions, a calibration time period was selected in which there was the greatest number of consecutive five-minute periods where there were no train crossings at the study site. The selected time period for calibration was Friday, April 25, 2003, from 8:10 a.m. to 9:20 a.m. Once the hourly volumes were entered for their respective movements, three calibrationspecific data collection points, as shown in Figure 9, were placed in the traffic network in VISSIM. These points collected output data from the model on mean speed of all vehicles and the number of vehicles. They were placed as close as possible to the locations where the actual pneumatic hoses were located in the field during data collection. VISSIM data collection points consist of a bar that is placed in the crosssection of a link, or roadway. As simulated vehicles cross the data collection bars, designated output information is collected about individual vehicles. It is this output data that is compared to the field data in the calibration/validation process. 4.2.1. Establishment of Calibration Parameters "The analyst should attempt to keep the set of adjustable parameters as small as possible to minimize the effort required to calibrate them. Whenever practical, the analyst should use observed field data to reflect local conditions. This observed data will serve as the nonadjustable values for certain calibration parameters, thus leaving the set of adjustable parameters to a minimum." (Dowling, Skabardonis, and Alexiadis, 2004) Two calibration parameters were selected for manipulation within the VISSIM model. These two calibration parameters are speed at turning movement locations and the two parts, additive and multiplicative, of desired safety distance (car following rule). These calibration parameters were systematically set at different values with each simulation run until the model duplicated the field conditions, within acceptable difference limits. In order for simulated vehicles to replicate field speeds at locations where speeds are known (in this case, where the double pneumatic hoses were placed), not only were the speeds on the roadways set, but reduced speed areas were incorporated. Reduced speed areas slow down vehicles through its area of application and allow a return to desired speed after the area is traversed. Nineteen reduced speed zones were placed in the traffic network surrounding the study site. Seven were placed at all turning movements (WBLT, WBRT, EBLT, EBRT, NBLT, and NBRT) at the Route 66/Enterprise Road intersection. Eleven were placed at all turning movements (EBLT, EBRT, WBLT, WBRT, NBLT, NBRT, SBLT, and SBRT) at the Butler Avenue/Enterprise RoadHuntington Drive intersection. One was placed on the Huntington Drive slip lane turning movement.
34
Figure 9: VISSIM Model Showing Data Collection Points A screenshot from the VISSIM model is shown, with the data collection points used to collect output activity information from the model. Data collection points labeled A, B, and C were used in collecting the field vehicle traffic data. These same locations were used to collect model output activity regarding mean speed and the number of vehicles for use in the calibration of the model. Figure 10, Figure 11, and Figure 12 on the following pages depict the locations of these reduced speed areas. Without reduced speed areas, the vehicles traverse the intersection at the free flow speed (which ranged from 35-45 miles per hour in this model) and the resulting data in VISSIM reflect unrealistic high speeds through the traffic network. By reducing the speed in which a vehicle can traverse the turning movements, the speeds on all roads reflected more closely the field speed data. The two parts, additive and multiplicative, of desired safety distance settings (car following rule), control the saturation flow rate of the model. As described in VISSIM software manual, these are model parameters under the Weidemann (1974) psychophysical driving behavior model, which the VISSIM model uses in its implementation (PTV Planung Transport Verkehr AG, 2003). The saturation flow rate defines the number of vehicles that can free flow through a VISSIM model during one hour. 35
Figure 10: VISSIM Model Screen Display At Route 66 and Enterprise Showing Reduced Speed Areas, Links, And Connectors A screenshot from the VISSIM model is shown, with the seven reduced speed areas outlined in green. These reduced speed areas are at the intersection of Route 66 and Enterprise Road. The blue lines depict "links" in the model, which serve as roadways (or sidewalk for pedestrians) containing a designated number of lanes. The purple lines are "connectors," which serve to connect links to one another and are used to model turning movements and changes in the number of lanes (lane additions or drops).
36
Figure 11: VISSIM Model Screen Display At Enterprise and Butler Showing Reduced Speed Areas, Links, And Connectors A screenshot from the VISSIM model is shown, indicating the 11 reduced speed areas at the intersection of Butler Avenue/Enterprise Road/Huntington Drive.
37
Figure 12: VISSIM Model Screen Display Showing Huntington Slip Lane Showing Reduced Speed Area, Links, And Connectors A screenshot from the VISSIM model is shown, with the reduced speed area on the slip lane of Huntington Drive, south of the Route 66/Enterprise Road intersection.
38
4.2.2. The Calibration Process After all field information, including geometrics and vehicular volume, was entered into the model, five seeds were run in VISSIM and the results (mean speed and number of vehicles) from each seed output were averaged. These averages for simulated vehicles were compared with the values for speed and number of vehicles obtained from field data. The target calibration objective of 10% or less was set for this difference. Ideally, this target objective could be met at the resolution of 5-minute aggregations; however, this level of data is rarely available and there is little experience in calibrating a model at this resolution. After several unsuccessful attempts, the resolution was changed to 15-minute aggregations. The variability of 5-minute aggregations was large, confounding the attempts to calibrate the model using them. Twenty-nine iterations were conducted until the target calibration objective was achieved. This calibration was achieved using the 15-minute aggregations. Once the calibration objective was achieved with five seed values, twenty seed values were simulated in VISSIM, which also met the calibration objective. 4.3. VISSIM MODEL VERIFICATION After the model is calibrated, its ability to generalize for different situations should be validated using a different data set. A second data set for validation was extracted from the field data for this purpose. The validation procedure used twenty seed values and the same model parameters finalized in the calibration process. The validation data set was for Thursday, April 24, 2003, from 3:50 p.m. to 4:35 p.m., which was also a time period where there were no trains in the traffic network. The validation vehicular data was entered into the calibrated VISSIM model and the results from twenty seeds were collected. This initial run did not meet the target objective of differences of 10% or less. Therefore, the calibration model was adjusted in various ways until, in all cases, the 10% target calibration objective was met. After four attempts, a fully calibrated model was found that also met the validation goal. In other words, the model met the 10% target for both the calibration and validation data sets.
39
(blank)
40
5.
EARLY WARNING SYSTEM
The research question focuses on taking actions before a train arrives at an at-grade crossing that will mitigate the congestion that occurs after the train passes. The actions to be taken are within the context of the traffic signal control system at the nearby intersection. A proposed solution to address the research question was to design and test an Early Warning System. 5.1. EARLY WARNING SYSTEM DESIGN CONSIDERATIONS To be of most use, an ideal EWS would conceptually have these features: 1. Simple and inexpensive to design, build, and install. 2. Capable of being maintained by existing maintenance technicians with little or no new training required. 3. Controlled by the highway agency without need for any changes to the railroad control system. 4. Able to maintain the time-tested safety aspects of current at-grade crossing highway and railroad control schemes. Functionally an ideal EWS would have these components: 1. Detection: Early detection of a train approaching the at-grade crossing. 2. Prediction: Prediction of when the train will arrive at the crossing and how long it will take to clear the crossing. 3. Congestion Mitigation: Changes in the normal intersection traffic control scheme before the train arrives that will reduce the congestion caused by a train after it has passed the crossing. 4. Safety: Minimize the possibility of a vehicle-train collision. The EWS reported here tests a system that will achieve the ideal features using the components listed above. Each component is itself is a subsystem and a major undertaking. Some components were addressed more fully than others in this research because of problems encountered and resource restraints. 5.2. EWS DETECTION SUBSYSTEM The EWS detection subsystem conceptually will detect an approaching train at a much greater distance from the crossing than a typical railroad detection system currently does. Additionally, this information must be communicated to the EWS prediction subsystem. The EWS prediction subsystem will require information about both the speed and the length of an approaching train. 5.2.1. Radar Detection and Wireless Communication A radio frequency (RF) Doppler radar detector has been used for train detection in previous research. Those systems were pioneered by Leonard Ruback at the Texas 41
Transportation Institute (Ruback 2001, TTI 2005-1). Ruback built systems in his lab from various components and has tested them in the field in various locations. Such an approach could be used; however, with the increasing use of radar speed detectors for ITS and enforcement uses1, off-the-shelf devices are now more readily available and would simplify the subsystem and make it easier to maintain. The radar detector would be pole mounted but would be located outside of railroad rightof-way (TTI 2005-2). It would be able to detect a train's presence and speed and send this information to the EWS prediction subsystem. It would also be able to send when the train was no longer detected. The detector would have the ability to induce the train's speed and possibly its length as well. If the length could not be induced by the sensor, it could be calculated by the prediction subsystem from the raw data collected by the detector, i.e., speed, time presence is first detected, and time presence is last detected. Another component needed for the EWS detection subsystem is a communication system that will send the detected train information to the EWS prediction subsystem. The prediction subsystem is probably best located in the same cabinet as the regular intersection traffic control system. Wireless sending and receiving devices will serve this purpose, when designed for outdoors field use such as in traffic applications. Spread spectrum technologies are one method typically employed. Several vendors offer products in this category using either direct sequence or frequency hopping techniques to produce the spread spectrum output. Spread spectrum equipment operating in the popular unlicensed 900 MHz ISM (Industrial, Scientific, and Medical) band would serve the purpose. These require a transmitter located on the pole with the detector and a receiver located in the intersection traffic control cabinet. Often line-of-sight must be maintained, which may require the use of repeater stations, as would long distances. However, these devices draw low power and can be solar powered. More than one pole-mounted sensor may be required. For example, a second sensor may be useful closer to the crossing. The data received from this second sensor could be used by the prediction subsystem to recalculate train arrival time and duration. If this has changed sufficiently, the actions taken by the congestion mitigation subsystem could be retimed or aborted. 5.2.2. Time Domain Reflectometry (TDR) Detection An experimental detection device has been developed under the IDEA2 program (TRB IDEA). The original intent of this system was to detect breaks in the railroad tracks. For this purpose, the device was mounted in the cab of the train driver. The device induces an electrical pulse into the rails ahead of the first locomotive axle. This pulse travels
1
Doppler radar devices are used in photo radar speed and red-light running systems, traffic monitoring systems for use by Traffic Control Centers, and variable message signs that display an approaching motorist of his vehicle speed. The Innovations Deserving Exploratory Analysis (IDEA) program provides start-up funding for promising, but unproven, innovations in surface transportation systems. The program is managed by the Transportation Research Board and supported by the Federal Railroad Administration, the Federal Transit Administration, and the Federal Motor Carrier Safety Administration.
2
42
forward through the rails until any significant electrical variation is encountered in the track, whereupon a portion of the pulse is reflected back to be received and analyzed at the train. The phase of the returning pulse will indicate if the hazard is a broken rail or track occupation, and the exact amount of time delay will give the distance ahead. If another train is ahead on the same track, the device can constantly calculate the distance and relative approach speed of the second train. In discussions with the developer of this device, Steven Turner of Analogic Engineering3, he indicated that this detection device might be used for the EWS detection subsystem. For this use, the detection device would be used at a fixed location at the crossing. The TDR detector would constantly sense for an approaching train. When one is detected, the detector would constantly calculate the speed and distance to the approaching train. It could continuously transmit this information and would therefore detect any change in speed that the EWS prediction subsystem could use to change or abort its earlier predictions. Since the TDR detector would be located at the crossing, communication to the nearby intersection traffic controller cabinet could be hardwired or wireless. However, if the length of the train is also needed, a second TDR detector would have to be installed some distance from the crossing. This second detector would detect the "back" of the train and transmit its data to the first TDR detector, located at the crossing, which would detect the "front" of the train. Since both detectors would be simultaneously giving the distance to the front and back of the train and the distance between the detectors is known, the length of the train can be calculated. This TDR system, configured for use in a train driver's cab, is currently undergoing testing at the Transportation Technology Center, Inc. (TTCI) in Pueblo, CO. TTCI focuses on railroad and transit research and operates a laboratory that includes 48 miles of railroad track to test a wide variety of rail components, including rolling stock, track components, signal, and safety devices. The TDR detection device has not been configured or scheduled for testing for use in the EWS detection subsystem and therefore its usefulness for this application remains unknown. Additionally, since it would be connected directly to the railroad's tracks, the system would not be controlled by the highway agency but would have to be controlled by the railroad company. But while the TDR detection device needs additional testing before it could be used, it does offer the significant potential benefit of providing continuous speed and distance data whereas a radar detector can only give "spot" speed/length information of the train where the detector is physically located. 5.3. EWS PREDICTION SUBSYSTEM An EWS prediction subsystem would be a small field-grade microprocessor located in the intersection traffic control cabinet. The data from the EWS detection subsystem would be received by the detection subsystem's data receiver located in the cabinet and ported to the microprocessor. The microprocessor would contain a clock that would
3
Steven Turner, Analogic Engineering, Inc., Guernsey, WY.
43
time-stamp incoming data. From this data it could predict the time the train would arrive at the crossing and the time interval before it cleared the crossing from a simple or sophisticated prediction algorithm. A simple approach, and one that has proved successful at other sites (Ruback 2001), is a simple speed versus distance to calculate time of arrival. Depending on the railroad speed limit changes between the detector and the crossing, this method could be within the accuracy needed. Railroad companies strictly enforce their speed limits and trains change speeds slowly. If a specific site has a complex set of parameters that might affect the speed of a train between the detector and the crossing, a more sophisticated algorithm could be developed to help account for this complexity. Conceptually, this is possible because a significant number of the parameters between the detector and the crossing are fixed, e.g., distances, speed limit change points, spurs, sidings, etc. These fixed parameters make it easier to accurately predict some of the changing variables. For example, if a train occasionally stops before it reaches the crossing, the behavior of a train that does so might have a recognizable pattern of speed changes at specific locations, etc. These speed changes might be detectable by positioning of multiple radar-type detectors at specific points or by using a continuous-type detector. When such a pattern was detected, the arrival prediction could be modified or aborted. 5.4. EWS CONGESTION MITIGATION SUBSYSTEM The microprocessor used for the EWS prediction subsystem would also contain the EWS congestion mitigation subsystem. Therefore, the predictions needed by the congestion mitigation subsystem would be available to it when needed. The congestion mitigation subsystem uses the EWS algorithm developed for the specific site. This system conceptually wraps around the EWS safety subsystem. Its purpose is to take actions when a train approaches before the normal train preemption occurs. These actions interrupt the normal traffic signal cycle and allocate the green time differently. If successful, this reallocation of green time before the train arrives will reduce the congestion that typically occurs after the train has passed. 5.4.1. Principle of Costs and Benefits At the research site, when a train is passing the crossing, the movements and phase numbers that are restricted from moving are WB LT (1), NB RT (8), NB LT (3), and EB RT (na), as shown by Figure 8. Therefore, it is these movements that are the focus of actions taken before the train arrives. Conceptually, this means that "extra" green time is given to these movements before the train arrives and the crossing gates come down. An important concept that governs giving "extra" green time to any movement is that it must be "stolen" from another movement. For example, in order to interrupt the normal cycle allocations of green and give WB LT (1) some "extra" green, it must be taken (stolen) from other movements in the normal cycle that was interrupted. If in this example, EB TH (2) was green and it was interrupted (cut short) to give WB LT (1), then the "extra" green given to WB LT (1) was "stolen" from EB TH (2). As a result, more vehicles would be delayed on EB TH (2) when green is "stolen" from it than if the normal cycle would not have been interrupted. This is the cost associated with 44
giving some "extra" green time to EB LT (1). The benefit is that "extra" green time will reduce the delay for those vehicles that receive it. 5.4.2. Measurement of Costs Versus Benefits In order for costs to be compared to benefits, a common measurement of both must be taken. These are called Measures of Effectiveness, or, they could be called Performance Measures (PMs). The MOE used must look at the intersection as a whole rather than as individual movements. Three MOEs were selected by the project's Technical Advisory Committee to be measured and analyzed for the study site. 1. Average Delay measured in seconds per vehicle, using all vehicles to pass through the intersection during a set period of time. 2. Average Travel Time measured in seconds per vehicle, using all vehicles to pass through the intersection during a set period of time. 3. Average Queue length measured in feet, using all vehicles to pass through the intersection during a set period of time. Two other MOEs were discussed by the TAC and would have been useful except that the VISSIM modeling environment used for the study would not capture them adequately. These were the Number of Cycles to Clear and Stopped Time. 5.4.3. Method to Capture Costs Versus Benefits -- Before and After Study In order to compare the costs versus the benefits of the EWS congestion mitigation subsystem, a method must be established to do this. This method is typically called a "Before and After" study. This title, while used in this report, is slightly misleading. Technically the method is a "With and Without" study. The Before (Without) analysis models the intersection without using the EWS. The After (With) analysis models the intersection using the EWS. An important principle is to duplicate exactly the entire modeling environment for both the Before and After analyses, only varying the specific EWS activities in the After analysis. This cannot be done in a field situation because many things change between the Before and After analyses besides the EWS activities. For example, the vehicle traffic changes since this is a stochastic process and is never duplicated exactly from one time to the next. Similarly, train traffic changes, as does a whole host of other factors. The only way to duplicate the entire environment exactly is to use a model that can duplicate all conditions exactly while changing only those needed for the After analysis. Microscopic simulation traffic models are the tools used for this purpose. One such modeling environment, VISSIM, was used for this study. It allows the capture of the MOEs of both the Before and After analyses and compare them. It is this comparison that yields the costs and benefits. 5.4.4. Stochastic Models Require Multiple Runs Microscopic traffic simulation models attempt to model the types of variability that actually occur at a site. For example, traffic varies from day to day and hour to hour. A typical peak hour traffic stream on Tuesday of one week, while similar to the traffic on the Tuesday of the following week, is not exactly the same. In fact, variability can be 45
significant. The model tries to capture this variability so that each time the model is run, it will vary the traffic flow in a definable, but stochastic way. Any run can be repeated exactly because it depends on an initial starting number, called the "seed." So if the same seed is used on a second run, it will produce the exact same results and MOEs as the first run. But if a different seed is used, the same model will vary the traffic flow and give different results. The strength of a microscopic simulation model is this variability. It provides a different, but probable, MOE output for each run. This models actual traffic in the field. So a scenario can be tested under different, but probable conditions, using a series of runs. The MOE from each run, however, is only a snapshot of what is happening. To get a true picture of what is happening, all the runs must be considered together. This can be done in several ways. The most useful is to average the MOEs from a series of runs and use this average MOE for analysis. However, in some cases the maximum and/or minimum value from a series of runs might be useful, for example in evaluating queue length. An accepted minimum number of runs varies from 5 to 10. The primary work done in this study uses 10 runs, but some of the secondary issues were explored with only 5 runs, which conserved resources. 5.4.5. Principle of Availability of Vehicles to Receive Benefit A subtle but critical principle when dealing with mitigating actions is that something done now will affect something that is forecast to happen in the future. In developing an EWS, the premise is that something is done before a train arrives at a crossing that will relieve congestion that will build up and be present once the train has cleared the crossing. Simply stated, the EWS attempts to move vehicles through the railroad crossing before the train arrives--vehicles that would normally have to wait until the train passed. The subtle, but necessary, condition for this to happen is that the vehicles that have to wait for the train to pass must arrive at the intersection early enough to be able to use the "extra" green they receive. In other words, unless a heavy volume of vehicles, which would be held up by the train, are available to move through the crossing when the EWS is initiated, then the "extra" green given to this movement is not used by a significant number of vehicles. The "extra" green time is not fully used because not enough vehicles are present to use it. This means that vehicles that arrive from right after the EWS has ended, until the train has passed, mainly cause the congestion. 5.5. EWS SAFETY SUBSYSTEM Safety is the primary objective of the special preemption control scheme currently used at an intersection when a train is passing at a nearby at-grade crossing. This scheme clears the tracks before the train arrives and withholds movement toward the crossing while the train is passing. It is triggered by a preemption signal sent by the railroad to the traffic signal controller. The traffic signal controller allows other preemptions, like the EWS, but requires each to have a priority assigned to it. The railroad preemption has a priority of one and overrides all other preemption signals as well as all other normal functions of the controller to 46
address the approaching train. The EWS maintains this safety by not interfering with either the preemption signal from the train or the signal controller's response to it. If the EWS is already activated when a railroad preemption signal is received, the EWS will be immediately terminated so the preemption control scheme can begin. Likewise if the preemption control scheme is running and the EWS sends a signal to begin, the EWS signal will be ignored until the train has cleared the crossing that the railroad preemption control scheme has finished. These actions are already a part of a standard controller logic and are not changed in any way by the EWS. Therefore, a key component of the safety subsystem of the EWS is to never interfere with the activation of the train preemption. By keeping this in place, the crossing safety experienced before an EWS is in